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TOPSIS</title> <meta name="description" content="Search results for: fuzzy TOPSIS"> <meta name="keywords" content="fuzzy TOPSIS"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="fuzzy TOPSIS"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 747</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: fuzzy TOPSIS</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">747</span> Group Decision Making through Interval-Valued Intuitionistic Fuzzy Soft Set TOPSIS Method Using New Hybrid Score Function</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Syed%20Talib%20Abbas%20Raza">Syed Talib Abbas Raza</a>, <a href="https://publications.waset.org/abstracts/search?q=Tahseen%20Ahmed%20Jilani"> Tahseen Ahmed Jilani</a>, <a href="https://publications.waset.org/abstracts/search?q=Saleem%20Abdullah"> Saleem Abdullah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents interval-valued intuitionistic fuzzy soft sets based TOPSIS method for group decision making. The interval-valued intuitionistic fuzzy soft set is a mutation of an interval-valued intuitionistic fuzzy set and soft set. In group decision making problems IVIFSS makes the process much more algebraically elegant. We have used weighted arithmetic averaging operator for aggregating the information and define a new Hybrid Score Function as metric tool for comparison between interval-valued intuitionistic fuzzy values. In an illustrative example we have applied the developed method to a criminological problem. We have developed a group decision making model for integrating the imprecise and hesitant evaluations of multiple law enforcement agencies working on target killing cases in the country. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=group%20decision%20making" title="group decision making">group decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=interval-valued%20intuitionistic%20fuzzy%20soft%20set" title=" interval-valued intuitionistic fuzzy soft set"> interval-valued intuitionistic fuzzy soft set</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=score%20function" title=" score function"> score function</a>, <a href="https://publications.waset.org/abstracts/search?q=criminology" title=" criminology"> criminology</a> </p> <a href="https://publications.waset.org/abstracts/21620/group-decision-making-through-interval-valued-intuitionistic-fuzzy-soft-set-topsis-method-using-new-hybrid-score-function" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21620.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">604</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">746</span> Triangular Hesitant Fuzzy TOPSIS Approach in Investment Projects Management</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Irina%20Khutsishvili">Irina Khutsishvili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The presented study develops a decision support methodology for multi-criteria group decision-making problem. The proposed methodology is based on the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) approach in the hesitant fuzzy environment. The main idea of decision-making problem is a selection of one best alternative or several ranking alternatives among a set of feasible alternatives. Typically, the process of decision-making is based on an evaluation of certain criteria. In many MCDM problems (such as medical diagnosis, project management, business and financial management, etc.), the process of decision-making involves experts' assessments. These assessments frequently are expressed in fuzzy numbers, confidence intervals, intuitionistic fuzzy values, hesitant fuzzy elements and so on. However, a more realistic approach is using linguistic expert assessments (linguistic variables). In the proposed methodology both the values and weights of the criteria take the form of linguistic variables, given by all decision makers. Then, these assessments are expressed in triangular fuzzy numbers. Consequently, proposed approach is based on triangular hesitant fuzzy TOPSIS decision-making model. Following the TOPSIS algorithm, first, the fuzzy positive ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are defined. Then the ranking of alternatives is performed in accordance with the proximity of their distances to the both FPIS and FNIS. Based on proposed approach the software package has been developed, which was used to rank investment projects in the real investment decision-making problem. The application and testing of the software were carried out based on the data provided by the ‘Bank of Georgia’. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20TOPSIS%20approach" title="fuzzy TOPSIS approach">fuzzy TOPSIS approach</a>, <a href="https://publications.waset.org/abstracts/search?q=investment%20project" title=" investment project"> investment project</a>, <a href="https://publications.waset.org/abstracts/search?q=linguistic%20variable" title=" linguistic variable"> linguistic variable</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20decision%20making" title=" multi-criteria decision making"> multi-criteria decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=triangular%20hesitant%20fuzzy%20set" title=" triangular hesitant fuzzy set"> triangular hesitant fuzzy set</a> </p> <a href="https://publications.waset.org/abstracts/59560/triangular-hesitant-fuzzy-topsis-approach-in-investment-projects-management" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59560.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">428</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">745</span> Earthquake Identification to Predict Tsunami in Andalas Island, Indonesia Using Back Propagation Method and Fuzzy TOPSIS Decision Seconder</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhamad%20Aris%20Burhanudin">Muhamad Aris Burhanudin</a>, <a href="https://publications.waset.org/abstracts/search?q=Angga%20Firmansyas"> Angga Firmansyas</a>, <a href="https://publications.waset.org/abstracts/search?q=Bagus%20Jaya%20Santosa"> Bagus Jaya Santosa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=earthquake" title="earthquake">earthquake</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20TOPSIS" title=" fuzzy TOPSIS"> fuzzy TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=tsunami" title=" tsunami"> tsunami</a> </p> <a href="https://publications.waset.org/abstracts/29246/earthquake-identification-to-predict-tsunami-in-andalas-island-indonesia-using-back-propagation-method-and-fuzzy-topsis-decision-seconder" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29246.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">493</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">744</span> An Integrated Fuzzy Inference System and Technique for Order of Preference by Similarity to Ideal Solution Approach for Evaluation of Lean Healthcare Systems </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aydin%20M.%20Torkabadi">Aydin M. Torkabadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ehsan%20Pourjavad"> Ehsan Pourjavad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A decade after the introduction of Lean in Saskatchewan’s public healthcare system, its effectiveness remains a controversial subject among health researchers, workers, managers, and politicians. Therefore, developing a framework to quantitatively assess the Lean achievements is significant. This study investigates the success of initiatives across Saskatchewan health regions by recognizing the Lean healthcare criteria, measuring the success levels, comparing the regions, and identifying the areas for improvements. This study proposes an integrated intelligent computing approach by applying Fuzzy Inference System (FIS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FIS is used as an efficient approach to assess the Lean healthcare criteria, and TOPSIS is applied for ranking the values in regards to the level of leanness. Due to the innate uncertainty in decision maker judgments on criteria, principals of the fuzzy theory are applied. Finally, FIS-TOPSIS was established as an efficient technique in determining the lean merit in healthcare systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=lean%20healthcare" title="lean healthcare">lean healthcare</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20computing" title=" intelligent computing"> intelligent computing</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20inference%20system" title=" fuzzy inference system"> fuzzy inference system</a>, <a href="https://publications.waset.org/abstracts/search?q=healthcare%20evaluation" title=" healthcare evaluation"> healthcare evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=technique%20for%20order%20of%20preference%20by%20similarity%20to%20ideal%20solution" title=" technique for order of preference by similarity to ideal solution"> technique for order of preference by similarity to ideal solution</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20decision%20making" title=" multi-criteria decision making"> multi-criteria decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=MCDM" title=" MCDM"> MCDM</a> </p> <a href="https://publications.waset.org/abstracts/91418/an-integrated-fuzzy-inference-system-and-technique-for-order-of-preference-by-similarity-to-ideal-solution-approach-for-evaluation-of-lean-healthcare-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91418.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">743</span> A Fuzzy TOPSIS Based Model for Safety Risk Assessment of Operational Flight Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Borjalilu">N. Borjalilu</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Rabiei"> P. Rabiei</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Enjoo"> A. Enjoo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=F-topsis" title="F-topsis">F-topsis</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20set" title=" fuzzy set"> fuzzy set</a>, <a href="https://publications.waset.org/abstracts/search?q=flight%20data%20monitoring%20%28FDM%29" title=" flight data monitoring (FDM)"> flight data monitoring (FDM)</a>, <a href="https://publications.waset.org/abstracts/search?q=flight%20safety" title=" flight safety"> flight safety</a> </p> <a href="https://publications.waset.org/abstracts/88089/a-fuzzy-topsis-based-model-for-safety-risk-assessment-of-operational-flight-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88089.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">168</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">742</span> A Comparative Analysis Approach Based on Fuzzy AHP, TOPSIS and PROMETHEE for the Selection Problem of GSCM Solutions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Omar%20Boutkhoum">Omar Boutkhoum</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Hanine"> Mohamed Hanine</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdessadek%20Bendarag"> Abdessadek Bendarag</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GSCM%20solutions" title="GSCM solutions">GSCM solutions</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20analysis" title=" multi-criteria analysis"> multi-criteria analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20system" title=" decision support system"> decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=FAHP" title=" FAHP"> FAHP</a>, <a href="https://publications.waset.org/abstracts/search?q=PROMETHEE" title=" PROMETHEE"> PROMETHEE</a> </p> <a href="https://publications.waset.org/abstracts/98205/a-comparative-analysis-approach-based-on-fuzzy-ahp-topsis-and-promethee-for-the-selection-problem-of-gscm-solutions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98205.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">163</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">741</span> Application of Fuzzy TOPSIS in Evaluating Green Transportation Options for Dhaka Megacity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md.%20Moniruzzaman">Md. Moniruzzaman</a>, <a href="https://publications.waset.org/abstracts/search?q=Thirayoot%20Limanond"> Thirayoot Limanond</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Being the most visible indicator, the transport system of a city points out how developed the city is. Dhaka megacity holds a mixed composition of motorized and non-motorized modes of transport and the number of vehicle figure is escalating over times. And this obviously poses associated environmental costs like air pollution, noise etc. which is degrading the quality of life in the city. Eventually sustainable transport or more importantly green transport from environmental point of view has become a prime choice to the transport professionals in order to cope up the crisis. Currently the city authority is planning to execute such sustainable transport systems that could serve the pressing demand of the present and meet the future needs effectively. This study focuses on the selection and evaluation of green transportation systems among potential alternatives on a priority basis. In this paper, Fuzzy TOPSIS - a multi-criteria decision method is presented to find out the most prioritized alternative. In the first step, Twenty-one individual specific criteria for sustainability assessment are selected. In the following step, experts provide linguistic ratings to the potential alternatives with respect to the selected criteria. The approach is used to generate aggregate scores for sustainability assessment and selection of the best alternative. In the third step, a sensitivity analysis is performed to understand the influence of criteria weights on the decision making process. The key strength of fuzzy TOPSIS approach is its practical applicability having a generation of good quality solution even under uncertainty. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=green%20transport" title="green transport">green transport</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20decision%20approach" title=" multi-criteria decision approach"> multi-criteria decision approach</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20transportation%20system" title=" urban transportation system"> urban transportation system</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainability%20assessment" title=" sustainability assessment"> sustainability assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20theory" title=" fuzzy theory"> fuzzy theory</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertainty" title=" uncertainty"> uncertainty</a> </p> <a href="https://publications.waset.org/abstracts/5644/application-of-fuzzy-topsis-in-evaluating-green-transportation-options-for-dhaka-megacity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5644.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">290</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">740</span> Risk Assessment of Building Information Modelling Adoption in Construction Projects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amirhossein%20Karamoozian">Amirhossein Karamoozian</a>, <a href="https://publications.waset.org/abstracts/search?q=Desheng%20Wu"> Desheng Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Behzad%20Abbasnejad"> Behzad Abbasnejad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Building information modelling (BIM) is a new technology to enhance the efficiency of project management in the construction industry. In addition to the potential benefits of this useful technology, there are various risks and obstacles to applying it in construction projects. In this study, a decision making approach is presented for risk assessment in BIM adoption in construction projects. Various risk factors of exerting BIM during different phases of the project lifecycle are identified with the help of Delphi method, experts’ opinions and related literature. Afterward, Shannon’s entropy and Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) are applied to derive priorities of the identified risk factors. Results indicated that lack of knowledge between professional engineers about workflows in BIM and conflict of opinions between different stakeholders are the risk factors with the highest priority. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=risk" title="risk">risk</a>, <a href="https://publications.waset.org/abstracts/search?q=BIM" title=" BIM"> BIM</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20TOPSIS" title=" fuzzy TOPSIS"> fuzzy TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=construction%20projects" title=" construction projects"> construction projects</a> </p> <a href="https://publications.waset.org/abstracts/115013/risk-assessment-of-building-information-modelling-adoption-in-construction-projects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/115013.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">229</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">739</span> Fuzzy Ideal Topological Spaces</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Koam">Ali Koam</a>, <a href="https://publications.waset.org/abstracts/search?q=Ismail%20Ibedou"> Ismail Ibedou</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20E.%20Abbas"> S. E. Abbas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, it is introduced the notion of r-fuzzy ideal separation axioms Tᵢi = 0; 1; 2 based on a fuzzy ideal I on a fuzzy topological space (X; τ). An r-fuzzy ideal connectedness related to the fuzzy ideal I is introduced which has relations with a previous r-fuzzy fuzzy connectedness. An r-fuzzy ideal compactness related to Ι is introduced which has also relations with many other types of fuzzy compactness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20ideal" title="fuzzy ideal">fuzzy ideal</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20separation%20axioms" title=" fuzzy separation axioms"> fuzzy separation axioms</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20compactness" title=" fuzzy compactness"> fuzzy compactness</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20connectedness" title=" fuzzy connectedness"> fuzzy connectedness</a> </p> <a href="https://publications.waset.org/abstracts/101746/fuzzy-ideal-topological-spaces" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101746.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">266</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">738</span> Investment Projects Selection Problem under Hesitant Fuzzy Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Irina%20Khutsishvili">Irina Khutsishvili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations, since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=In%20the%20present%20research" title="In the present research">In the present research</a>, <a href="https://publications.waset.org/abstracts/search?q=a%20decision%20support%20methodology%20for%20the%20multi-attribute%20group%20decision-making%20%28MAGDM%29%20problem%20is%20developed" title=" a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed"> a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed</a>, <a href="https://publications.waset.org/abstracts/search?q=namely%20for%20the%20selection%20of%20investment%20projects.%20%0D%0AThe%20objective%20of%20the%20investment%20project%20selection%20problem%20is%20to%20choose%20the%20best%20project%20among%20the%20set%20of%20projects" title=" namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects"> namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects</a>, <a href="https://publications.waset.org/abstracts/search?q=seeking%20investment" title=" seeking investment"> seeking investment</a>, <a href="https://publications.waset.org/abstracts/search?q=or%20to%20rank%20all%20projects%20in%20descending%20order.%20The%20project%20selection%20is%20made%20considering%20a%20set%20of%20weighted%20attributes.%20To%20evaluate%20the%20attributes%20in%20our%20approach" title=" or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach"> or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach</a>, <a href="https://publications.waset.org/abstracts/search?q=expert%20assessments%20are%20used.%20In%20the%20proposed%20methodology" title=" expert assessments are used. In the proposed methodology"> expert assessments are used. In the proposed methodology</a>, <a href="https://publications.waset.org/abstracts/search?q=lingual%20expressions%20%28linguistic%20terms%29%20given%20by%20all%20experts%20are%20used%20as%20initial%20attribute%20evaluations%20since%20they%20are%20the%20most%20natural%20and%20convenient%20representation%20of%20experts%27%20evaluations.%20Then%20lingual%20evaluations%20are%20converted%20into%20trapezoidal%20fuzzy%20numbers" title=" lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers"> lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers</a>, <a href="https://publications.waset.org/abstracts/search?q=and%20the%20aggregate%20trapezoidal%20hesitant%20fuzzy%20decision%20matrix%20will%20be%20built.%20The%20case%20is%20considered%20when%20information%20on%20the%20attribute%20weights%20is%20completely%20unknown.%20The%20attribute%20weights%20are%20identified%20based%20on%20the%20De%20Luca%20and%20Termini%20information%20entropy%20concept" title=" and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept"> and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept</a>, <a href="https://publications.waset.org/abstracts/search?q=determined%20in%20the%20context%20of%20hesitant%20fuzzy%20sets.%20The%20decisions%20are%20made%20using%20the%20extended%20Technique%20for%20Order%20Performance%20by%20Similarity%20to%20Ideal%20Solution%20%28TOPSIS%29%20method%20under%20a%20hesitant%20fuzzy%20environment.%20Hence" title=" determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence"> determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence</a>, <a href="https://publications.waset.org/abstracts/search?q=a%20methodology%20is%20based%20on%20a%20trapezoidal%20valued%20hesitant%20fuzzy%20TOPSIS%20decision-making%20model%20with%20entropy%20weights.%20The%20ranking%20of%20alternatives%20is%20performed%20by%20the%20proximity%20of%20their%20distances%20to%20both%20the%20fuzzy%20positive-ideal%20solution%20%28FPIS%29%20and%20the%20fuzzy%20negative-ideal%20solution%20%28FNIS%29.%20For%20this%20purpose" title=" a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose"> a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20weighted%20hesitant%20Hamming%20distance%20is%20used.%20An%20example%20of%20investment%20decision-making%20is%20shown%20that%20clearly%20explains%20the%20procedure%20of%20the%20proposed%20methodology." title=" the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology."> the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.</a> </p> <a href="https://publications.waset.org/abstracts/161078/investment-projects-selection-problem-under-hesitant-fuzzy-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161078.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">117</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">737</span> Proactive Pure Handoff Model with SAW-TOPSIS Selection and Time Series Predict</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harold%20V%C3%A1squez">Harold Vásquez</a>, <a href="https://publications.waset.org/abstracts/search?q=Cesar%20Hern%C3%A1ndez"> Cesar Hernández</a>, <a href="https://publications.waset.org/abstracts/search?q=Ingrid%20P%C3%A1ez"> Ingrid Páez </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20radio" title="cognitive radio">cognitive radio</a>, <a href="https://publications.waset.org/abstracts/search?q=spectrum%20handoff" title=" spectrum handoff"> spectrum handoff</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20making" title=" decision making"> decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series" title=" time series"> time series</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless%20networks" title=" wireless networks"> wireless networks</a> </p> <a href="https://publications.waset.org/abstracts/33216/proactive-pure-handoff-model-with-saw-topsis-selection-and-time-series-predict" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33216.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">487</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">736</span> Sensitivity Analysis in Fuzzy Linear Programming Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20H.%20Nasseri">S. H. Nasseri</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Ebrahimnejad"> A. Ebrahimnejad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy set theory has been applied to many fields, such as operations research, control theory, and management sciences. In this paper, we consider two classes of fuzzy linear programming (FLP) problems: Fuzzy number linear programming and linear programming with trapezoidal fuzzy variables problems. We state our recently established results and develop fuzzy primal simplex algorithms for solving these problems. Finally, we give illustrative examples. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20linear%20programming" title="fuzzy linear programming">fuzzy linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20numbers" title=" fuzzy numbers"> fuzzy numbers</a>, <a href="https://publications.waset.org/abstracts/search?q=duality" title=" duality"> duality</a>, <a href="https://publications.waset.org/abstracts/search?q=sensitivity%20analysis" title=" sensitivity analysis"> sensitivity analysis</a> </p> <a href="https://publications.waset.org/abstracts/16916/sensitivity-analysis-in-fuzzy-linear-programming-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16916.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">565</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">735</span> Some New Hesitant Fuzzy Sets Operator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20S.%20Thakur">G. S. Thakur </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, four new operators (O1, O2, O3, O4) are proposed, defined and considered to study the new properties and identities on hesitant fuzzy sets. These operators are useful for different operation on hesitant fuzzy sets. The various theorems are proved using the new operators. The study of the proposed new operators has opened a new area of research and applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vague%20sets" title="vague sets">vague sets</a>, <a href="https://publications.waset.org/abstracts/search?q=hesitant%20fuzzy%20sets" title=" hesitant fuzzy sets"> hesitant fuzzy sets</a>, <a href="https://publications.waset.org/abstracts/search?q=intuitionistic%20fuzzy%20set" title=" intuitionistic fuzzy set"> intuitionistic fuzzy set</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20sets" title=" fuzzy sets"> fuzzy sets</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20multisets" title=" fuzzy multisets "> fuzzy multisets </a> </p> <a href="https://publications.waset.org/abstracts/5174/some-new-hesitant-fuzzy-sets-operator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5174.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">285</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">734</span> Application of Fuzzy Multiple Criteria Decision Making for Flooded Risk Region Selection in Thailand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Waraporn%20Wimuktalop">Waraporn Wimuktalop</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research will select regions which are vulnerable to flooding in different level. Mathematical principles will be systematically and rationally utilized as a tool to solve problems of selection the regions. Therefore the method called Multiple Criteria Decision Making (MCDM) has been chosen by having two analysis standards, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and AHP (Analytic Hierarchy Process). There are three criterions that have been considered in this research. The first criterion is climate which is the rainfall. The second criterion is geography which is the height above mean sea level. The last criterion is the land utilization which both forest and agriculture use. The study found that the South has the highest risk of flooding, then the East, the Centre, the North-East, the West and the North, respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multiple%20criteria%20decision%20making" title="multiple criteria decision making">multiple criteria decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=analytic%20hierarchy%20process" title=" analytic hierarchy process"> analytic hierarchy process</a>, <a href="https://publications.waset.org/abstracts/search?q=flooding" title=" flooding"> flooding</a> </p> <a href="https://publications.waset.org/abstracts/74376/application-of-fuzzy-multiple-criteria-decision-making-for-flooded-risk-region-selection-in-thailand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74376.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">233</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">733</span> The Location Problem of Electric Vehicle Charging Stations: A Case Study of Istanbul</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M%C3%BCjde%20Erol%20Genevois">Müjde Erol Genevois</a>, <a href="https://publications.waset.org/abstracts/search?q=Hatice%20Kocaman"> Hatice Kocaman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Growing concerns about the increasing consumption of fossil energy and the improved recognition of environmental protection require sustainable road transportation technology. Electric vehicles (EVs) can contribute to improve environmental sustainability and to solve the energy problem with the right infrastructure. The problem of where to locate electric vehicle charging station can be grouped as decision-making problems because of including many criteria and alternatives that have to be considered simultaneously. The purpose of this paper is to present an integrated AHP and TOPSIS model to rank the optimal sites of EVs charging station in Istanbul, Turkey. Ten different candidate points and three decision criteria are identified. The performances of each candidate points with respect to criteria are obtained according to AHP calculations. These performances are used as an input for TOPSIS method to rank the candidate points. It is obtained accurate and robust results by integrating AHP and TOPSIS methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electric%20vehicle%20charging%20station%20%28EVCS%29" title="electric vehicle charging station (EVCS)">electric vehicle charging station (EVCS)</a>, <a href="https://publications.waset.org/abstracts/search?q=AHP" title=" AHP"> AHP</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=location%20selection" title=" location selection"> location selection</a> </p> <a href="https://publications.waset.org/abstracts/79222/the-location-problem-of-electric-vehicle-charging-stations-a-case-study-of-istanbul" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79222.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">324</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">732</span> Merit Measures and Validation in Employee Evaluation and Selection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wilson%20P.%20R.%20Malebye">Wilson P. R. Malebye</a>, <a href="https://publications.waset.org/abstracts/search?q=Solly%20M.%20Seeletse"> Solly M. Seeletse </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Applicants for space in selection problems are usually compared subjectively, and the selection made are not reliable and often cannot be verified scientifically. The paper illustrates objective selection by involving a mathematical measure in selecting a candidate applying for a job, and then using other two independent measures, validates the choice made. The scientific process followed is SToR (SAW, TOPSIS, WP) in which Simple Additive Weighting (SAW) is used to select, and the TOPSIS (technique for order preference by similarity to ideal solution) and weighted product (WP) are used to validate. A practical exercise was obtained from a factual selection problem in a recruitment task undertaken in an organization in which the authors consulted, and their Human Resources (HR) department wanted to check if their selection was justifiable. The result was that our approach was consistent and convincing to that HR, and theirs was not because our selection was satisfactory while theirs could not be corroborated using any method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=candidate%20selection" title="candidate selection">candidate selection</a>, <a href="https://publications.waset.org/abstracts/search?q=SToR" title=" SToR"> SToR</a>, <a href="https://publications.waset.org/abstracts/search?q=SW" title=" SW"> SW</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=WP" title=" WP"> WP</a> </p> <a href="https://publications.waset.org/abstracts/30729/merit-measures-and-validation-in-employee-evaluation-and-selection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30729.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">345</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">731</span> 2D Structured Non-Cyclic Fuzzy Graphs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=T.%20Pathinathan">T. Pathinathan</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Peter"> M. Peter</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy graphs incorporate concepts from graph theory with fuzzy principles. In this paper, we make a study on the properties of fuzzy graphs which are non-cyclic and are of two-dimensional in structure. In particular, this paper presents 2D structure or the structure of double layer for a non-cyclic fuzzy graph whose underlying crisp graph is non-cyclic. In any graph structure, introducing 2D structure may lead to an inherent cycle. We propose relevant conditions for 2D structured non-cyclic fuzzy graphs. These conditions are extended even to fuzzy graphs of the 3D structure. General theoretical properties that are studied for any fuzzy graph are verified to 2D structured or double layered fuzzy graphs. Concepts like Order, Degree, Strong and Size for a fuzzy graph are studied for 2D structured or double layered non-cyclic fuzzy graphs. Using different types of fuzzy graphs, the proposed concepts relating to 2D structured fuzzy graphs are verified. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=double%20layered%20fuzzy%20graph" title="double layered fuzzy graph">double layered fuzzy graph</a>, <a href="https://publications.waset.org/abstracts/search?q=double%20layered%20non%E2%80%93cyclic%20fuzzy%20graph" title=" double layered non–cyclic fuzzy graph"> double layered non–cyclic fuzzy graph</a>, <a href="https://publications.waset.org/abstracts/search?q=order" title=" order"> order</a>, <a href="https://publications.waset.org/abstracts/search?q=degree%20and%20size" title=" degree and size"> degree and size</a> </p> <a href="https://publications.waset.org/abstracts/80562/2d-structured-non-cyclic-fuzzy-graphs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80562.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">400</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">730</span> Solving Fuzzy Multi-Objective Linear Programming Problems with Fuzzy Decision Variables</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahnaz%20Hosseinzadeh">Mahnaz Hosseinzadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Aliyeh%20Kazemi"> Aliyeh Kazemi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a method is proposed for solving Fuzzy Multi-Objective Linear Programming problems (FMOLPP) with fuzzy right hand side and fuzzy decision variables. To illustrate the proposed method, it is applied to the problem of selecting suppliers for an automotive parts producer company in Iran in order to find the number of optimal orders allocated to each supplier considering the conflicting objectives. Finally, the obtained results are discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20multi-objective%20linear%20programming%20problems" title="fuzzy multi-objective linear programming problems">fuzzy multi-objective linear programming problems</a>, <a href="https://publications.waset.org/abstracts/search?q=triangular%20fuzzy%20numbers" title=" triangular fuzzy numbers"> triangular fuzzy numbers</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20ranking" title=" fuzzy ranking"> fuzzy ranking</a>, <a href="https://publications.waset.org/abstracts/search?q=supplier%20selection%20problem" title=" supplier selection problem"> supplier selection problem</a> </p> <a href="https://publications.waset.org/abstracts/54020/solving-fuzzy-multi-objective-linear-programming-problems-with-fuzzy-decision-variables" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54020.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">383</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">729</span> Complex Fuzzy Evolution Equation with Nonlocal Conditions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelati%20El%20Allaoui">Abdelati El Allaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Said%20Melliani"> Said Melliani</a>, <a href="https://publications.waset.org/abstracts/search?q=Lalla%20Saadia%20Chadli"> Lalla Saadia Chadli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objective of this paper is to study the existence and uniqueness of Mild solutions for a complex fuzzy evolution equation with nonlocal conditions that accommodates the notion of fuzzy sets defined by complex-valued membership functions. We first propose definition of complex fuzzy strongly continuous semigroups. We then give existence and uniqueness result relevant to the complex fuzzy evolution equation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Complex%20fuzzy%20evolution%20equations" title="Complex fuzzy evolution equations">Complex fuzzy evolution equations</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlocal%20conditions" title=" nonlocal conditions"> nonlocal conditions</a>, <a href="https://publications.waset.org/abstracts/search?q=mild%20solution" title=" mild solution"> mild solution</a>, <a href="https://publications.waset.org/abstracts/search?q=complex%20fuzzy%20semigroups" title=" complex fuzzy semigroups"> complex fuzzy semigroups</a> </p> <a href="https://publications.waset.org/abstracts/59900/complex-fuzzy-evolution-equation-with-nonlocal-conditions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59900.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">281</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">728</span> Fuzzy Multi-Component DEA with Shared and Undesirable Fuzzy Resources</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jolly%20Puri">Jolly Puri</a>, <a href="https://publications.waset.org/abstracts/search?q=Shiv%20Prasad%20Yadav"> Shiv Prasad Yadav</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-component%20DEA" title="multi-component DEA">multi-component DEA</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20multi-component%20DEA" title=" fuzzy multi-component DEA"> fuzzy multi-component DEA</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20resources" title=" fuzzy resources"> fuzzy resources</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20making%20units%20%28DMUs%29" title=" decision making units (DMUs)"> decision making units (DMUs)</a> </p> <a href="https://publications.waset.org/abstracts/9809/fuzzy-multi-component-dea-with-shared-and-undesirable-fuzzy-resources" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9809.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">407</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">727</span> A Sustainable Supplier Selection and Order Allocation Based on Manufacturing Processes and Product Tolerances: A Multi-Criteria Decision Making and Multi-Objective Optimization Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ravi%20Patel">Ravi Patel</a>, <a href="https://publications.waset.org/abstracts/search?q=Krishna%20K.%20Krishnan"> Krishna K. Krishnan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AHP" title="AHP">AHP</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20set%20theory" title=" fuzzy set theory"> fuzzy set theory</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20decision%20making" title=" multi-criteria decision making"> multi-criteria decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20integer%20linear%20programming" title=" multi-objective integer linear programming"> multi-objective integer linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a> </p> <a href="https://publications.waset.org/abstracts/85835/a-sustainable-supplier-selection-and-order-allocation-based-on-manufacturing-processes-and-product-tolerances-a-multi-criteria-decision-making-and-multi-objective-optimization-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/85835.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">170</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">726</span> A Fuzzy Nonlinear Regression Model for Interval Type-2 Fuzzy Sets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20Poleshchuk">O. Poleshchuk</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Komarov"> E. Komarov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=interval%20type-2%20fuzzy%20sets" title="interval type-2 fuzzy sets">interval type-2 fuzzy sets</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression" title=" fuzzy regression"> fuzzy regression</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20interval" title=" weighted interval"> weighted interval</a> </p> <a href="https://publications.waset.org/abstracts/6138/a-fuzzy-nonlinear-regression-model-for-interval-type-2-fuzzy-sets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6138.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">373</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">725</span> A Fuzzy Mathematical Model for Order Acceptance and Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=E.%20Koyuncu">E. Koyuncu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20mathematical%20programming" title="fuzzy mathematical programming">fuzzy mathematical programming</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20ranking" title=" fuzzy ranking"> fuzzy ranking</a>, <a href="https://publications.waset.org/abstracts/search?q=order%20acceptance" title=" order acceptance"> order acceptance</a>, <a href="https://publications.waset.org/abstracts/search?q=single%20machine%20scheduling" title=" single machine scheduling"> single machine scheduling</a> </p> <a href="https://publications.waset.org/abstracts/62385/a-fuzzy-mathematical-model-for-order-acceptance-and-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62385.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">338</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">724</span> Prioritization in a Maintenance, Repair and Overhaul (MRO) System Based on Fuzzy Logic at Iran Khodro (IKCO)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Izadi%20Banafsheh">Izadi Banafsheh</a>, <a href="https://publications.waset.org/abstracts/search?q=Sedaghat%20Reza"> Sedaghat Reza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Maintenance, Repair, and Overhaul (MRO) of machinery are a key recent issue concerning the automotive industry. It has always been a debated question what order or priority should be adopted for the MRO of machinery. This study attempts to examine several criteria including process sensitivity, average time between machine failures, average duration of repair, availability of parts, availability of maintenance personnel and workload through a literature review and experts survey so as to determine the condition of the machine. According to the mentioned criteria, the machinery were ranked in four modes below: A) Need for inspection, B) Need for minor repair, C) Need for part replacement, and D) Need for major repair. The Fuzzy AHP was employed to determine the weighting of criteria. At the end, the obtained weights were ranked through the AHP for each criterion, three groups were specified: shaving machines, assembly and painting in four modes. The statistical population comprises the elite in the Iranian automotive industry at IKCO covering operation managers, CEOs and maintenance professionals who are highly specialized in MRO and perfectly knowledgeable in how the machinery function. The information required for this study were collected from both desk research and field review, which eventually led to construction of a questionnaire handed out to the sample respondents in order to collect information on the subject matter. The results of the AHP for weighting the criteria revealed that the availability of maintenance personnel was the top priority at coefficient of 0.206, while the process sensitivity took the last priority at coefficient of 0.066. Furthermore, the results of TOPSIS for prioritizing the IKCO machinery suggested that at the mode where there is need for inspection, the assembly machines took the top priority while paining machines took the third priority. As for the mode where there is need for minor repairs, the assembly machines took the top priority while the third priority belonged to the shaving machines. As for the mode where there is need for parts replacement, the assembly machines took the top priority while the third belonged to the paining machinery. Finally, as for the mode where there is need for major repair, the assembly machines took the top priority while the third belonged to the paining machinery. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=maintenance" title="maintenance">maintenance</a>, <a href="https://publications.waset.org/abstracts/search?q=repair" title=" repair"> repair</a>, <a href="https://publications.waset.org/abstracts/search?q=overhaul" title=" overhaul"> overhaul</a>, <a href="https://publications.waset.org/abstracts/search?q=MRO" title=" MRO"> MRO</a>, <a href="https://publications.waset.org/abstracts/search?q=prioritization%20of%20machinery" title=" prioritization of machinery"> prioritization of machinery</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=AHP" title=" AHP"> AHP</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a> </p> <a href="https://publications.waset.org/abstracts/35379/prioritization-in-a-maintenance-repair-and-overhaul-mro-system-based-on-fuzzy-logic-at-iran-khodro-ikco" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35379.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">286</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">723</span> Operational Matrix Method for Fuzzy Fractional Reaction Diffusion Equation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sachin%20Kumar">Sachin Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20PDE" title="fractional PDE">fractional PDE</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20valued%20function" title=" fuzzy valued function"> fuzzy valued function</a>, <a href="https://publications.waset.org/abstracts/search?q=diffusion%20equation" title=" diffusion equation"> diffusion equation</a>, <a href="https://publications.waset.org/abstracts/search?q=Legendre%20polynomial" title=" Legendre polynomial"> Legendre polynomial</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20method" title=" spectral method"> spectral method</a> </p> <a href="https://publications.waset.org/abstracts/125273/operational-matrix-method-for-fuzzy-fractional-reaction-diffusion-equation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/125273.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">201</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">722</span> An Application of Content Analysis, SWOT Analysis, and the TOPSIS Method: A Case Study of the 'Tourism Ambassador' Program in Indonesia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gilang%20Maulana%20Majid">Gilang Maulana Majid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> If a government program remains scientifically uncontested for a long time, it is likely that its effects will be far from expected as there is no concrete evaluation of the steps being taken. This article identifies how such a theory aptly describes the case of the 'tourism ambassador' program in Indonesia. Being set out as one of the tourism promotional means of many regional governments in Indonesia, this program is heavily criticized for being ineffective despite a large number of budgets being spent on an annual basis. Taking the program as a case study, this article applies content analysis, SWOT analysis, and TOPSIS as data analysis methods, with a total of 56 tourism ambassadors invited to become coders, respondents, and/or interviewees in this research. The study reveals the SWOT of the program, recognizes four strategies that can be taken to optimize the program's effects and prioritizes a strategy based on the preferences of the involved tourism ambassadors using TOPSIS. It is found that incorporation of technology such as the creation of an online platform is, among others, the most expected approach to be taken to solve the problems concerning tourism ambassador program. However, based on the costs and benefits of each strategy presented in the current study, each alternative appears to have trade-offs between one and another. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Indonesia" title="Indonesia">Indonesia</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20strategies" title=" optimization strategies"> optimization strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=%27Tourism%20Ambassador%27%20program" title=" 'Tourism Ambassador' program"> 'Tourism Ambassador' program</a>, <a href="https://publications.waset.org/abstracts/search?q=SWOT-TOPSIS" title=" SWOT-TOPSIS"> SWOT-TOPSIS</a> </p> <a href="https://publications.waset.org/abstracts/109243/an-application-of-content-analysis-swot-analysis-and-the-topsis-method-a-case-study-of-the-tourism-ambassador-program-in-indonesia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109243.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">166</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">721</span> Single Valued Neutrosophic Hesitant Fuzzy Rough Set and Its Application</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20M.%20Alsager">K. M. Alsager</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20O.%20Alshehri"> N. O. Alshehri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we proposed the notion of single valued neutrosophic hesitant fuzzy rough set, by combining single valued neutrosophic hesitant fuzzy set and rough set. The combination of single valued neutrosophic hesitant fuzzy set and rough set is a powerful tool for dealing with uncertainty, granularity and incompleteness of knowledge in information systems. We presented both definition and some basic properties of the proposed model. Finally, we gave a general approach which is applied to a decision making problem in disease diagnoses, and demonstrated the effectiveness of the approach by a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=single%20valued%20neutrosophic%20fuzzy%20set" title="single valued neutrosophic fuzzy set">single valued neutrosophic fuzzy set</a>, <a href="https://publications.waset.org/abstracts/search?q=single%20valued%20neutrosophic%20fuzzy%20hesitant%20set" title=" single valued neutrosophic fuzzy hesitant set"> single valued neutrosophic fuzzy hesitant set</a>, <a href="https://publications.waset.org/abstracts/search?q=rough%20set" title=" rough set"> rough set</a>, <a href="https://publications.waset.org/abstracts/search?q=single%20valued%20neutrosophic%20hesitant%20fuzzy%20rough%20set" title=" single valued neutrosophic hesitant fuzzy rough set"> single valued neutrosophic hesitant fuzzy rough set</a> </p> <a href="https://publications.waset.org/abstracts/104161/single-valued-neutrosophic-hesitant-fuzzy-rough-set-and-its-application" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/104161.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">272</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">720</span> Fuzzy Control and Pertinence Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Luiz%20F.%20J.%20Maia">Luiz F. J. Maia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an approach to fuzzy control, with the use of new pertinence functions, applied in the case of an inverted pendulum. Appropriate definitions of pertinence functions to fuzzy sets make possible the implementation of the controller with only one control rule, resulting in a smooth control surface. The fuzzy control system can be implemented with analog devices, affording a true real-time performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=control%20surface" title="control surface">control surface</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20control" title=" fuzzy control"> fuzzy control</a>, <a href="https://publications.waset.org/abstracts/search?q=Inverted%20pendulum" title=" Inverted pendulum"> Inverted pendulum</a>, <a href="https://publications.waset.org/abstracts/search?q=pertinence%20functions" title=" pertinence functions"> pertinence functions</a> </p> <a href="https://publications.waset.org/abstracts/2467/fuzzy-control-and-pertinence-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2467.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">449</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">719</span> Ranking Effective Factors on Strategic Planning to Achieve Organization Objectives in Fuzzy Multivariate Decision-Making Technique</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elahe%20Memari">Elahe Memari</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Aslizadeh"> Ahmad Aslizadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Memari"> Ahmad Memari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Today strategic planning is counted as the most important duties of senior directors in each organization. Strategic planning allows the organizations to implement compiled strategies and reach higher competitive benefits than their competitors. The present research work tries to prepare and rank the strategies form effective factors on strategic planning in fulfillment of the State Road Management and Transportation Organization in order to indicate the role of organizational factors in efficiency of the process to organization managers. Connection between six main factors in fulfillment of State Road Management and Transportation Organization were studied here, including Improvement of Strategic Thinking in senior managers, improvement of the organization business process, rationalization of resources allocation in different parts of the organization, coordination and conformity of strategic plan with organization needs, adjustment of organization activities with environmental changes, reinforcement of organizational culture. All said factors approved by implemented tests and then ranked using fuzzy multivariate decision-making technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20TOPSIS" title="Fuzzy TOPSIS">Fuzzy TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=improvement%20of%20organization%20business%20process" title=" improvement of organization business process"> improvement of organization business process</a>, <a href="https://publications.waset.org/abstracts/search?q=multivariate%20decision-making" title=" multivariate decision-making"> multivariate decision-making</a>, <a href="https://publications.waset.org/abstracts/search?q=strategic%20planning" title=" strategic planning"> strategic planning</a> </p> <a href="https://publications.waset.org/abstracts/55021/ranking-effective-factors-on-strategic-planning-to-achieve-organization-objectives-in-fuzzy-multivariate-decision-making-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55021.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">423</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">718</span> A Fuzzy Kernel K-Medoids Algorithm for Clustering Uncertain Data Objects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Behnam%20Tavakkol">Behnam Tavakkol</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Uncertain data mining algorithms use different ways to consider uncertainty in data such as by representing a data object as a sample of points or a probability distribution. Fuzzy methods have long been used for clustering traditional (certain) data objects. They are used to produce non-crisp cluster labels. For uncertain data, however, besides some uncertain fuzzy k-medoids algorithms, not many other fuzzy clustering methods have been developed. In this work, we develop a fuzzy kernel k-medoids algorithm for clustering uncertain data objects. The developed fuzzy kernel k-medoids algorithm is superior to existing fuzzy k-medoids algorithms in clustering data sets with non-linearly separable clusters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clustering%20algorithm" title="clustering algorithm">clustering algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20methods" title=" fuzzy methods"> fuzzy methods</a>, <a href="https://publications.waset.org/abstracts/search?q=kernel%20k-medoids" title=" kernel k-medoids"> kernel k-medoids</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertain%20data" title=" uncertain data"> uncertain data</a> </p> <a href="https://publications.waset.org/abstracts/123501/a-fuzzy-kernel-k-medoids-algorithm-for-clustering-uncertain-data-objects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/123501.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">215</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20TOPSIS&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20TOPSIS&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20TOPSIS&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20TOPSIS&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20TOPSIS&page=6">6</a></li> <li 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