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interval-valued intuitionistic fuzzy soft set</title> <meta name="description" content="Search results for: interval-valued intuitionistic fuzzy soft set"> <meta name="keywords" content="interval-valued intuitionistic fuzzy soft set"> <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 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</div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: interval-valued intuitionistic fuzzy soft set</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1658</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">1657</span> Approach to Formulate Intuitionistic Fuzzy Regression Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Liang-Hsuan%20Chen">Liang-Hsuan Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Sheng-Shing%20Nien"> Sheng-Shing Nien</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches. <p class="card-text"><strong>Keywords:</strong> <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=intuitionistic%20fuzzy%20number" title=" intuitionistic fuzzy number"> intuitionistic fuzzy number</a>, <a href="https://publications.waset.org/abstracts/search?q=intuitionistic%20fuzzy%20regression" title=" intuitionistic fuzzy regression"> intuitionistic fuzzy regression</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20programming%20method" title=" mathematical programming method"> mathematical programming method</a> </p> <a href="https://publications.waset.org/abstracts/123234/approach-to-formulate-intuitionistic-fuzzy-regression-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/123234.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">138</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">1656</span> An Algorithm to Find Fractional Edge Domination Number and Upper Fractional Edge Domination Number of an Intuitionistic Fuzzy Graph</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Karunambigai%20Mevani%20Govindasamy">Karunambigai Mevani Govindasamy</a>, <a href="https://publications.waset.org/abstracts/search?q=Sathishkumar%20Ayyappan"> Sathishkumar Ayyappan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we formulate the algorithm to find out the dominating function parameters of Intuitionistic Fuzzy Graphs(IFG). The methodology we adopted here is converting any physical problem into an IFG, and that has been transformed into Intuitionistic Fuzzy Matrix. Using Linear Program Solver software (LiPS), we found the defined parameters for the given IFG. We obtained these parameters for a path and cycle IFG. This study can be extended to other varieties of IFG. In particular, we obtain the definition of edge dominating function, minimal edge dominating function, fractional edge domination number (γ_if^') and upper fractional edge domination number (Γ_if^') of an intuitionistic fuzzy graph. Also, we formulated an algorithm which is appropriate to work on LiPS to find fractional edge domination number and upper fractional edge domination number of an IFG. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20edge%20domination%20number" title="fractional edge domination number">fractional edge domination number</a>, <a href="https://publications.waset.org/abstracts/search?q=intuitionistic%20fuzzy%20cycle" title=" intuitionistic fuzzy cycle"> intuitionistic fuzzy cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=intuitionistic%20fuzzy%20graph" title=" intuitionistic fuzzy graph"> intuitionistic fuzzy graph</a>, <a href="https://publications.waset.org/abstracts/search?q=intuitionistic%20fuzzy%20path" title=" intuitionistic fuzzy path"> intuitionistic fuzzy path</a> </p> <a href="https://publications.waset.org/abstracts/112004/an-algorithm-to-find-fractional-edge-domination-number-and-upper-fractional-edge-domination-number-of-an-intuitionistic-fuzzy-graph" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/112004.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">174</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">1655</span> An Integrated Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE) Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Babak%20Daneshvar%20Rouyendegh">Babak Daneshvar Rouyendegh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Decision-Makers%20%28DMs%29" title="Decision-Makers (DMs)">Decision-Makers (DMs)</a>, <a href="https://publications.waset.org/abstracts/search?q=Multi-Criteria%20Decision-Making%20%28MCDM%29" title=" Multi-Criteria Decision-Making (MCDM)"> Multi-Criteria Decision-Making (MCDM)</a>, <a href="https://publications.waset.org/abstracts/search?q=Intuitionistic%20Fuzzy%20Elimination%20Et%20Choix%20Traduisant%20La%20REalite%20%28IFELECTRE%29" title=" Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE)"> Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE)</a>, <a href="https://publications.waset.org/abstracts/search?q=Intuitionistic%20Fuzzy%20Numbers%20%28IFN%29" title=" Intuitionistic Fuzzy Numbers (IFN)"> Intuitionistic Fuzzy Numbers (IFN)</a> </p> <a href="https://publications.waset.org/abstracts/23210/an-integrated-intuitionistic-fuzzy-elimination-et-choix-traduisant-la-realite-ifelectre-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23210.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">678</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">1654</span> A Fuzzy Programming Approach for Solving Intuitionistic Fuzzy Linear Fractional Programming Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sujeet%20Kumar%20Singh">Sujeet Kumar Singh</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> This paper develops an approach for solving intuitionistic fuzzy linear fractional programming (IFLFP) problem where the cost of the objective function, the resources, and the technological coefficients are triangular intuitionistic fuzzy numbers. Here, the IFLFP problem is transformed into an equivalent crisp multi-objective linear fractional programming (MOLFP) problem. By using fuzzy mathematical programming approach the transformed MOLFP problem is reduced into a single objective linear programming (LP) problem. The proposed procedure is illustrated through a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=triangular%20intuitionistic%20fuzzy%20number" title="triangular intuitionistic fuzzy number">triangular intuitionistic fuzzy number</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20programming%20problem" title=" linear programming problem"> linear programming problem</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20objective%20linear%20programming%20problem" title=" multi objective linear programming problem"> multi objective linear programming problem</a>, <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=membership%20function" title=" membership function"> membership function</a> </p> <a href="https://publications.waset.org/abstracts/16411/a-fuzzy-programming-approach-for-solving-intuitionistic-fuzzy-linear-fractional-programming-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16411.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">566</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">1653</span> Extended Intuitionistic Fuzzy VIKOR Method in Group Decision Making: The Case of Vendor Selection Decision</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nastaran%20Hajiheydari">Nastaran Hajiheydari</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Soltani%20Delgosha"> Mohammad Soltani Delgosha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Vendor (supplier) selection is a group decision-making (GDM) process, in which, based on some predetermined criteria, the experts’ preferences are provided in order to rank and choose the most desirable suppliers. In the real business environment, our attitudes or our choices would be made in an uncertain and indecisive situation could not be expressed in a crisp framework. Intuitionistic fuzzy sets (IFSs) could handle such situations in the best way. VIKOR method was developed to solve multi-criteria decision-making (MCDM) problems. This method, which is used to determine the compromised feasible solution with respect to the conflicting criteria, introduces a multi-criteria ranking index based on the particular measure of 'closeness' to the 'ideal solution'. Until now, there has been a little investigation of VIKOR with IFS, therefore we extended the intuitionistic fuzzy (IF) VIKOR to solve vendor selection problem under IF GDM environment. The present study intends to develop an IF VIKOR method in a GDM situation. Therefore, a model is presented to calculate the criterion weights based on entropy measure. Then, the interval-valued intuitionistic fuzzy weighted geometric (IFWG) operator utilized to obtain the total decision matrix. In the next stage, an approach based on the positive idle intuitionistic fuzzy number (PIIFN) and negative idle intuitionistic fuzzy number (NIIFN) was developed. Finally, the application of the proposed method to solve a vendor selection problem illustrated. <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=intuitionistic%20fuzzy%20set" title=" intuitionistic fuzzy set"> intuitionistic fuzzy set</a>, <a href="https://publications.waset.org/abstracts/search?q=intuitionistic%20fuzzy%20entropy%20measure" title=" intuitionistic fuzzy entropy measure"> intuitionistic fuzzy entropy measure</a>, <a href="https://publications.waset.org/abstracts/search?q=vendor%20selection" title=" vendor selection"> vendor selection</a>, <a href="https://publications.waset.org/abstracts/search?q=VIKOR" title=" VIKOR"> VIKOR</a> </p> <a href="https://publications.waset.org/abstracts/95995/extended-intuitionistic-fuzzy-vikor-method-in-group-decision-making-the-case-of-vendor-selection-decision" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95995.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">155</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">1652</span> Recruitment Model (FSRM) for Faculty Selection Based on Fuzzy Soft</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> This paper presents a Fuzzy Soft Recruitment Model (FSRM) for faculty selection of MHRD technical institutions. The selection criteria are based on 4-tier flexible structure in the institutions. The Advisory Committee on Faculty Recruitment (ACoFAR) suggested nine criteria for faculty in the proposed FSRM. The model Fuzzy Soft is proposed with consultation of ACoFAR based on selection criteria. The Fuzzy Soft distance similarity measures are applied for finding best faculty from the applicant pool. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20soft%20set" title="fuzzy soft set">fuzzy soft 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%20soft%20distance" title=" fuzzy soft distance"> fuzzy soft distance</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20soft%20similarity%20measures" title=" fuzzy soft similarity measures"> fuzzy soft similarity measures</a>, <a href="https://publications.waset.org/abstracts/search?q=ACoFAR" title=" ACoFAR"> ACoFAR</a> </p> <a href="https://publications.waset.org/abstracts/12838/recruitment-model-fsrm-for-faculty-selection-based-on-fuzzy-soft" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12838.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">347</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">1651</span> An Integreated Intuitionistic Fuzzy ELECTRE Model for Multi-Criteria Decision-Making</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Babek%20Erdebilli">Babek Erdebilli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using IFE (Elimination Et Choix Traduisant La Realite (ELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy Numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20decision-making" title="multi-criteria decision-making">multi-criteria decision-making</a>, <a href="https://publications.waset.org/abstracts/search?q=IFE" title=" IFE"> IFE</a>, <a href="https://publications.waset.org/abstracts/search?q=DM%E2%80%99s" title=" DM’s"> DM’s</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20electre%20model" title=" fuzzy electre model"> fuzzy electre model</a> </p> <a href="https://publications.waset.org/abstracts/19788/an-integreated-intuitionistic-fuzzy-electre-model-for-multi-criteria-decision-making" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19788.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">651</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">1650</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">1649</span> Application of IF Rough Data on Knowledge Towards Malaria of Rural Tribal Communities in Tripura</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chhaya%20Gangwal">Chhaya Gangwal</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20N.%20Bhaumik"> R. N. Bhaumik</a>, <a href="https://publications.waset.org/abstracts/search?q=Shishir%20Kumar"> Shishir Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Handling uncertainty and impreciseness of knowledge appears to be a challenging task in Information Systems. Intuitionistic fuzzy (IF) and rough set theory enhances databases by allowing it for the management of uncertainty and impreciseness. This paper presents a new efficient query optimization technique for the multi-valued or imprecise IF rough database. The usefulness of this technique was illustrated on malaria knowledge from the rural tribal communities of Tripura where most of the information is multi-valued and imprecise. Then, the querying about knowledge on malaria is executed into SQL server to make the implementation of IF rough data querying simpler. <p class="card-text"><strong>Keywords:</strong> <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=rough%20set" title=" rough set"> rough set</a>, <a href="https://publications.waset.org/abstracts/search?q=relational%20database" title=" relational database"> relational database</a>, <a href="https://publications.waset.org/abstracts/search?q=IF%20rough%20relational%20database" title=" IF rough relational database"> IF rough relational database</a> </p> <a href="https://publications.waset.org/abstracts/1814/application-of-if-rough-data-on-knowledge-towards-malaria-of-rural-tribal-communities-in-tripura" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1814.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">444</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">1648</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">1647</span> Decision-Making using Fuzzy Linguistic Hypersoft Set Topology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Saqlain">Muhammad Saqlain</a>, <a href="https://publications.waset.org/abstracts/search?q=Poom%20Kumam"> Poom Kumam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Language being an abstract system and creative act, is quite complicated as its meaning varies depending on the context. The context is determined by the empirical knowledge of a person, which is derived from observation and experience. About further subdivided attributes, the decision-making challenges may entail quantitative and qualitative factors. However, because there is no norm for putting a numerical value on language, existing approaches cannot carry out the operations of linguistic knowledge. The assigning of mathematical values (fuzzy, intuitionistic, and neutrosophic) to any decision-making problem; without considering any rule of linguistic knowledge is ambiguous and inaccurate. Thus, this paper aims to provide a generic model for these issues. This paper provides the linguistic set structure of the fuzzy hypersoft set (FLHSS) to solve decision-making issues. We have proposed the definition some basic operations like AND, NOT, OR, AND, compliment, negation, etc., along with Topology and examples, and properties. Secondly, the operational laws for the fuzzy linguistic hypersoft set have been proposed to deal with the decision-making issues. Implementing proposed aggregate operators and operational laws can be used to convert linguistic quantifiers into numerical values. This will increase the accuracy and precision of the fuzzy hypersoft set structure to deal with decision-making issues. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=linguistic%20quantifiers" title="linguistic quantifiers">linguistic quantifiers</a>, <a href="https://publications.waset.org/abstracts/search?q=aggregate%20operators" title=" aggregate operators"> aggregate operators</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-criteria%20decision%20making%20%28mcdm%29." title=" multi-criteria decision making (mcdm)."> multi-criteria decision making (mcdm).</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20topology" title=" fuzzy topology"> fuzzy topology</a> </p> <a href="https://publications.waset.org/abstracts/164348/decision-making-using-fuzzy-linguistic-hypersoft-set-topology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164348.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">97</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">1646</span> Performance Comparison of AODV and Soft AODV Routing Protocol</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abhishek">Abhishek</a>, <a href="https://publications.waset.org/abstracts/search?q=Seema%20Devi"> Seema Devi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jyoti%20Ohri"> Jyoti Ohri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A mobile ad hoc network (MANET) represents a system of wireless mobile nodes that can self-organize freely and dynamically into arbitrary and temporary network topology. Unlike a wired network, wireless network interface has limited transmission range. Routing is the task of forwarding data packets from source to a given destination. Ad-hoc On Demand Distance Vector (AODV) routing protocol creates a path for a destination only when it required. This paper describes the implementation of AODV routing protocol using MATLAB-based Truetime simulator. In MANET's node movements are not fixed while they are random in nature. Hence intelligent techniques i.e. fuzzy and ANFIS are used to optimize the transmission range. In this paper, we compared the transmission range of AODV, fuzzy AODV and ANFIS AODV. For soft computing AODV, we have taken transmitted power and received threshold as input and transmission range as output. ANFIS gives better results as compared to fuzzy AODV. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ANFIS" title="ANFIS">ANFIS</a>, <a href="https://publications.waset.org/abstracts/search?q=AODV" title=" AODV"> AODV</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy" title=" fuzzy"> fuzzy</a>, <a href="https://publications.waset.org/abstracts/search?q=MANET" title=" MANET"> MANET</a>, <a href="https://publications.waset.org/abstracts/search?q=reactive%20routing%20protocol" title=" reactive routing protocol"> reactive routing protocol</a>, <a href="https://publications.waset.org/abstracts/search?q=routing%20protocol" title=" routing protocol"> routing protocol</a>, <a href="https://publications.waset.org/abstracts/search?q=truetime" title=" truetime "> truetime </a> </p> <a href="https://publications.waset.org/abstracts/25434/performance-comparison-of-aodv-and-soft-aodv-routing-protocol" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25434.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">498</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">1645</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">1644</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">1643</span> Fuzzy Logic Based Sliding Mode Controller for a New Soft Switching Boost Converter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azam%20Salimi">Azam Salimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Majid%20Delshad"> Majid Delshad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a modified design of a sliding mode controller based on fuzzy logic for a New ZVThigh step up DC-DC Converter . Here a proportional - integral (PI)-type current mode control is employed and a sliding mode controller is designed utilizing fuzzy algorithm. Sliding mode controller guarantees robustness against all variations and fuzzy logic helps to reduce chattering phenomenon due to sliding controller, in that way efficiency increases and error, voltage and current ripples decreases. The proposed system is simulated using MATLAB / SIMULINK. This model is tested under variations of input and reference voltages and it was found that in comparison with conventional sliding mode controllers they perform better. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=switching%20mode%20power%20supplies" title="switching mode power supplies">switching mode power supplies</a>, <a href="https://publications.waset.org/abstracts/search?q=DC-DC%20converters" title=" DC-DC converters"> DC-DC converters</a>, <a href="https://publications.waset.org/abstracts/search?q=sliding%20mode%20control" title=" sliding mode control"> sliding mode control</a>, <a href="https://publications.waset.org/abstracts/search?q=robustness" title=" robustness"> robustness</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=current%20mode%20control" title=" current mode control"> current mode control</a>, <a href="https://publications.waset.org/abstracts/search?q=non-linear%20behavior" title=" non-linear behavior"> non-linear behavior</a> </p> <a href="https://publications.waset.org/abstracts/28763/fuzzy-logic-based-sliding-mode-controller-for-a-new-soft-switching-boost-converter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28763.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">538</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">1642</span> The Various Forms of a Soft Set and Its Extension in Medical Diagnosis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Biplab%20Singha">Biplab Singha</a>, <a href="https://publications.waset.org/abstracts/search?q=Mausumi%20Sen"> Mausumi Sen</a>, <a href="https://publications.waset.org/abstracts/search?q=Nidul%20Sinha"> Nidul Sinha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to deal with the impreciseness and uncertainty of a system, D. Molodtsov has introduced the concept of ‘Soft Set’ in the year 1999. Since then, a number of related definitions have been conceptualized. This paper includes a study on various forms of Soft Sets with examples. The paper contains the concepts of domain and co-domain of a soft set, conversion to one-one and onto function, matrix representation of a soft set and its relation with one-one function, upper and lower triangular matrix, transpose and Kernel of a soft set. This paper also gives the idea of the extension of soft sets in medical diagnosis. Here, two soft sets related to disease and symptoms are considered and using AND operation and OR operation, diagnosis of the disease is calculated through appropriate examples. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=kernel%20of%20a%20soft%20set" title="kernel of a soft set">kernel of a soft set</a>, <a href="https://publications.waset.org/abstracts/search?q=soft%20set" title=" soft set"> soft set</a>, <a href="https://publications.waset.org/abstracts/search?q=transpose%20of%20a%20soft%20set" title=" transpose of a soft set"> transpose of a soft set</a>, <a href="https://publications.waset.org/abstracts/search?q=upper%20and%20lower%20triangular%20matrix%20of%20a%20soft%20set" title=" upper and lower triangular matrix of a soft set"> upper and lower triangular matrix of a soft set</a> </p> <a href="https://publications.waset.org/abstracts/59585/the-various-forms-of-a-soft-set-and-its-extension-in-medical-diagnosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59585.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">344</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">1641</span> Fuzzy-Sliding Controller Design for Induction Motor Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Bouferhane">M. Bouferhane</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Boukhebza"> A. Boukhebza</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Hatab"> L. Hatab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=linear%20induction%20motor" title="linear induction motor">linear induction motor</a>, <a href="https://publications.waset.org/abstracts/search?q=vector%20control" title=" vector control"> vector control</a>, <a href="https://publications.waset.org/abstracts/search?q=backstepping" title=" backstepping"> backstepping</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy-sliding%20mode%20control" title=" fuzzy-sliding mode control"> fuzzy-sliding mode control</a> </p> <a href="https://publications.waset.org/abstracts/44272/fuzzy-sliding-controller-design-for-induction-motor-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44272.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">489</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">1640</span> Soft Computing Employment to Optimize Safety Stock Levels in Supply Chain Dairy Product under Supply and Demand Uncertainty</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Riyadh%20Jamegh">Riyadh Jamegh</a>, <a href="https://publications.waset.org/abstracts/search?q=Alla%20Eldin%20Kassam"> Alla Eldin Kassam</a>, <a href="https://publications.waset.org/abstracts/search?q=Sawsan%20Sabih"> Sawsan Sabih</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=inventory%20optimization" title="inventory optimization">inventory optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=soft%20computing" title=" soft computing"> soft computing</a>, <a href="https://publications.waset.org/abstracts/search?q=safety%20stock%20optimization" title=" safety stock optimization"> safety stock optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=dairy%20industries%20inventory%20optimization" title=" dairy industries inventory optimization"> dairy industries inventory optimization</a> </p> <a href="https://publications.waset.org/abstracts/102674/soft-computing-employment-to-optimize-safety-stock-levels-in-supply-chain-dairy-product-under-supply-and-demand-uncertainty" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102674.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">125</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">1639</span> Application of Soft Sets to Non-Associative Rings</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Inayatur%20Rehman">Inayatur Rehman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Molodtstove developed the theory of soft sets which can be seen as an effective tool to deal with uncertainties. Since the introduction of this concept, the application of soft sets has been restricted to associative algebraic structures (groups, semi groups, associative rings, semi-rings etc.). Acceptably, though the study of soft sets, where the base set of parameters is a commutative structure, has attracted the attention of many researchers for more than one decade. But on the other hand there are many sets which are naturally endowed by two compatible binary operations forming a non-associative ring and we may dig out examples which investigate a non-associative structure in the context of soft sets. Thus it seems natural to apply the concept of soft sets to non-commutative and non-associative structures. In present paper, we make a new approach to apply Molodtsoves notion of soft sets to LA-ring (a class of non-associative ring). We extend the study of soft commutative rings from theoretical aspect. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=soft%20sets" title="soft sets">soft sets</a>, <a href="https://publications.waset.org/abstracts/search?q=LA-rings" title=" LA-rings"> LA-rings</a>, <a href="https://publications.waset.org/abstracts/search?q=soft%20LA-rings" title=" soft LA-rings"> soft LA-rings</a>, <a href="https://publications.waset.org/abstracts/search?q=soft%20ideals" title=" soft ideals"> soft ideals</a>, <a href="https://publications.waset.org/abstracts/search?q=soft%20prime%20ideals" title=" soft prime ideals"> soft prime ideals</a>, <a href="https://publications.waset.org/abstracts/search?q=idealistic%0D%0Asoft%20LA-rings" title=" idealistic soft LA-rings"> idealistic soft LA-rings</a>, <a href="https://publications.waset.org/abstracts/search?q=LA-ring%20homomorphism" title=" LA-ring homomorphism "> LA-ring homomorphism </a> </p> <a href="https://publications.waset.org/abstracts/33475/application-of-soft-sets-to-non-associative-rings" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33475.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">463</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">1638</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">1637</span> Applicability of Fuzzy Logic for Intrusion Detection in Mobile Adhoc Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ruchi%20Makani">Ruchi Makani</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20V.%20R.%20%20Reddy"> B. V. R. Reddy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AODV" title="AODV">AODV</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20adhoc%20networks" title=" mobile adhoc networks"> mobile adhoc networks</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title=" intrusion detection"> intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=anomaly%20detection" title=" anomaly detection"> anomaly detection</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=fuzzy%20membership%20function" title=" fuzzy membership function"> fuzzy membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20inference%20system" title=" fuzzy inference system"> fuzzy inference system</a> </p> <a href="https://publications.waset.org/abstracts/94205/applicability-of-fuzzy-logic-for-intrusion-detection-in-mobile-adhoc-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94205.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">177</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">1636</span> Comparative Study on Manet Using Soft Computing Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amarjit%20Singh">Amarjit Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Tripatdeep%20Singh%20Dua"> Tripatdeep Singh Dua</a>, <a href="https://publications.waset.org/abstracts/search?q=Vikas%20Attri"> Vikas Attri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mobile Ad-hoc Network is a combination of several nodes that create dynamically a specific network without using any base infrastructure. In this study all the mobile nodes can depended upon each other to send any data. Mobile host can pick up data and forwarding to their destination path. Basically MANET depend upon their Quality of Service which is highly constraints to the user. To give better services we need to improve the QOS. In these days MANET QOS requirement to use soft computing techniques. These techniques depend upon their specific requirement and which exists using MANET concepts. Using a soft computing techniques various protocol and algorithms may be considered. In this paper, we provide comparative study review of existing work done in MANET using various kind of soft computing techniques. Our review research is based on their specific protocol or algorithm which provide concern solution of QOS need. We discuss about various protocol through which routing in MANET. In Second section we clear the concepts of Soft Computing and their types. In third section we review the MANET using different kind of soft computing techniques work done before. In forth section we need to understand the concept of QoS requirement which exists in MANET and we done comparative study on different protocol used before and last we conclude the purpose of using MANET with soft computing techniques metrics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mobile%20ad-hoc%20network" title="mobile ad-hoc network">mobile ad-hoc network</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20improved%20genetic%20approach" title=" fuzzy improved genetic approach"> fuzzy improved genetic approach</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=routing%20protocol" title=" routing protocol"> routing protocol</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless%20mesh%20network" title=" wireless mesh network"> wireless mesh network</a> </p> <a href="https://publications.waset.org/abstracts/40121/comparative-study-on-manet-using-soft-computing-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40121.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">349</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">1635</span> Decision Making System for Clinical Datasets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Bharathiraja">P. Bharathiraja </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making. <p class="card-text"><strong>Keywords:</strong> <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=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=normalization" title=" normalization"> normalization</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20rule" title=" fuzzy rule"> fuzzy rule</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/31212/decision-making-system-for-clinical-datasets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31212.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">517</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">1634</span> Movement Optimization of Robotic Arm Movement Using Soft Computing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=V.%20K.%20Banga">V. K. Banga</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=kinematics" title="kinematics">kinematics</a>, <a href="https://publications.waset.org/abstracts/search?q=robotic%20arm" title=" robotic arm"> robotic arm</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a> </p> <a href="https://publications.waset.org/abstracts/52861/movement-optimization-of-robotic-arm-movement-using-soft-computing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52861.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">297</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">1633</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">1632</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">1631</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">1630</span> A Fermatean Fuzzy MAIRCA Approach for Maintenance Strategy Selection of Process Plant Gearbox Using Sustainability Criteria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Soumava%20Boral">Soumava Boral</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanjay%20K.%20Chaturvedi"> Sanjay K. Chaturvedi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ian%20Howard"> Ian Howard</a>, <a href="https://publications.waset.org/abstracts/search?q=Kristoffer%20McKee"> Kristoffer McKee</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20N.%20A.%20Naikan"> V. N. A. Naikan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fermatean%20fuzzy%20sets" title="Fermatean fuzzy sets">Fermatean fuzzy sets</a>, <a href="https://publications.waset.org/abstracts/search?q=Fermatean%20fuzzy%20MAIRCA" title=" Fermatean fuzzy MAIRCA"> Fermatean fuzzy MAIRCA</a>, <a href="https://publications.waset.org/abstracts/search?q=maintenance%20strategy%20selection" title=" maintenance strategy selection"> maintenance strategy selection</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainable%20manufacturing" title=" sustainable manufacturing"> sustainable manufacturing</a>, <a href="https://publications.waset.org/abstracts/search?q=MCDM" title=" MCDM "> MCDM </a> </p> <a href="https://publications.waset.org/abstracts/125323/a-fermatean-fuzzy-mairca-approach-for-maintenance-strategy-selection-of-process-plant-gearbox-using-sustainability-criteria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/125323.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">138</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">1629</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 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