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fuzzy integral approach</title> <meta name="description" content="Search results for: non-additive fuzzy integral approach"> <meta name="keywords" content="non-additive fuzzy integral approach"> <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 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method="get" action="https://publications.waset.org/abstracts/search"> <div 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="non-additive fuzzy integral approach"> <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> 14966</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: non-additive fuzzy integral approach</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">14966</span> Third Party Logistics (3PL) Selection Criteria for an Indian Heavy Industry Using SEM </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nadama%20Kumar">Nadama Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Parthiban"> P. Parthiban</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Niranjan"> T. Niranjan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the present paper, we propose an incorporated approach for 3PL supplier choice that suits the distinctive strategic needs of the outsourcing organization in southern part of India. Four fundamental criteria have been used in particular Performance, IT, Service and Intangible. These are additionally subdivided into fifteen sub-criteria. The proposed strategy coordinates Structural Equation Modeling (SEM) and Non-additive Fuzzy Integral strategies. The presentation of fluffiness manages the unclearness of human judgments. The SEM approach has been used to approve the determination criteria for the proposed show though the Non-additive Fuzzy Integral approach uses the SEM display contribution to assess a supplier choice score. The case organization has a exclusive vertically integrated assembly that comprises of several companies focusing on a slight array of the value chain. To confirm manufacturing and logistics proficiency, it significantly relies on 3PL suppliers to attain supply chain superiority. However, 3PL supplier selection is an intricate decision-making procedure relating multiple selection criteria. The goal of this work is to recognize the crucial 3PL selection criteria by using the non-additive fuzzy integral approach. Unlike the outmoded multi criterion decision-making (MCDM) methods which frequently undertake independence among criteria and additive importance weights, the nonadditive fuzzy integral is an effective method to resolve the dependency among criteria, vague information, and vital fuzziness of human judgment. In this work, we validate an empirical case that engages the nonadditive fuzzy integral to assess the importance weight of selection criteria and indicate the most suitable 3PL supplier. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=3PL" title="3PL">3PL</a>, <a href="https://publications.waset.org/abstracts/search?q=non-additive%20fuzzy%20integral%20approach" title=" non-additive fuzzy integral approach"> non-additive fuzzy integral approach</a>, <a href="https://publications.waset.org/abstracts/search?q=SEM" title=" SEM"> SEM</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy" title=" fuzzy"> fuzzy</a> </p> <a href="https://publications.waset.org/abstracts/79215/third-party-logistics-3pl-selection-criteria-for-an-indian-heavy-industry-using-sem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79215.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">280</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">14965</span> H∞ Fuzzy Integral Power Control for DFIG Wind Energy System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Chayaopas">N. Chayaopas</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20Assawinchaichote"> W. Assawinchaichote</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to maximize energy capturing from wind energy, controlling the doubly fed induction generator to have optimal power from the wind, generator speed and output electrical power control in wind energy system have a great importance due to the nonlinear behavior of wind velocities. In this paper purposes the design of a control scheme is developed for power control of wind energy system via H∞ fuzzy integral controller. Firstly, the nonlinear system is represented in term of a TS fuzzy control design via linear matrix inequality approach to find the optimal controller to have an H∞ performance are derived. The proposed control method extract the maximum energy from the wind and overcome the nonlinearity and disturbances problems of wind energy system which give good tracking performance and high efficiency power output of the DFIG. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=doubly%20fed%20induction%20generator" title="doubly fed induction generator">doubly fed induction generator</a>, <a href="https://publications.waset.org/abstracts/search?q=H-infinity%20fuzzy%20integral%20control" title=" H-infinity fuzzy integral control"> H-infinity fuzzy integral control</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20matrix%20inequality" title=" linear matrix inequality"> linear matrix inequality</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20energy%20system" title=" wind energy system"> wind energy system</a> </p> <a href="https://publications.waset.org/abstracts/57959/h-fuzzy-integral-power-control-for-dfig-wind-energy-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57959.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">14964</span> Design of a Cooperative Neural Network, Particle Swarm Optimization (PSO) and Fuzzy Based Tracking Control for a Tilt Rotor Unmanned Aerial Vehicle </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mostafa%20Mjahed">Mostafa Mjahed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Tilt Rotor UAVs (Unmanned Aerial Vehicles) are naturally unstable and difficult to maneuver. The purpose of this paper is to design controllers for the stabilization and trajectory tracking of this type of UAV. To this end, artificial intelligence methods have been exploited. First, the dynamics of this UAV was modeled using the Lagrange-Euler method. The conventional method based on Proportional, Integral and Derivative (PID) control was applied by decoupling the different flight modes. To improve stability and trajectory tracking of the Tilt Rotor, the fuzzy approach and the technique of multilayer neural networks (NN) has been used. Thus, Fuzzy Proportional Integral and Derivative (FPID) and Neural Network-based Proportional Integral and Derivative controllers (NNPID) have been developed. The meta-heuristic approach based on Particle Swarm Optimization (PSO) method allowed adjusting the setting parameters of NNPID controller, giving us an improved NNPID-PSO controller. Simulation results under the Matlab environment show the efficiency of the approaches adopted. Besides, the Tilt Rotor UAV has become stable and follows different types of trajectories with acceptable precision. The Fuzzy, NN and NN-PSO-based approaches demonstrated their robustness because the presence of the disturbances did not alter the stability or the trajectory tracking of the Tilt Rotor UAV. <p class="card-text"><strong>Keywords:</strong> <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=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=PSO" title=" PSO"> PSO</a>, <a href="https://publications.waset.org/abstracts/search?q=PID" title=" PID"> PID</a>, <a href="https://publications.waset.org/abstracts/search?q=trajectory%20tracking" title=" trajectory tracking"> trajectory tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=tilt-rotor%20UAV" title=" tilt-rotor UAV"> tilt-rotor UAV</a> </p> <a href="https://publications.waset.org/abstracts/115686/design-of-a-cooperative-neural-network-particle-swarm-optimization-pso-and-fuzzy-based-tracking-control-for-a-tilt-rotor-unmanned-aerial-vehicle" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/115686.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">120</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">14963</span> Fuzzy Logic and Control Strategies on a Sump</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nasser%20Mohamed%20Ramli">Nasser Mohamed Ramli</a>, <a href="https://publications.waset.org/abstracts/search?q=Nurul%20Izzati%20Zulkifli"> Nurul Izzati Zulkifli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sump can be defined as a reservoir which contains slurry; a mixture of solid and liquid or water, in it. Sump system is an unsteady process owing to the level response. Sump level shall be monitored carefully by using a good controller to avoid overflow. The current conventional controllers would not be able to solve problems with large time delay and nonlinearities, Fuzzy Logic controller is tested to prove its ability in solving the listed problems of slurry sump. Therefore, in order to justify the effectiveness and reliability of these controllers, simulation of the sump system was created by using MATLAB and the results were compared. According to the result obtained, instead of Proportional-Integral (PI) and Proportional-Integral and Derivative (PID), Fuzzy Logic controller showed the best result by offering quick response of 0.32 s for step input and 5 s for pulse generator, by producing small Integral Absolute Error (IAE) values that are 0.66 and 0.36 respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy" title="fuzzy">fuzzy</a>, <a href="https://publications.waset.org/abstracts/search?q=sump" title=" sump"> sump</a>, <a href="https://publications.waset.org/abstracts/search?q=level" title=" level"> level</a>, <a href="https://publications.waset.org/abstracts/search?q=controller" title=" controller"> controller</a> </p> <a href="https://publications.waset.org/abstracts/75241/fuzzy-logic-and-control-strategies-on-a-sump" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75241.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">243</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">14962</span> Improving Load Frequency Control of Multi-Area Power System by Considering Uncertainty by Using Optimized Type 2 Fuzzy Pid Controller with the Harmony Search Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehrdad%20Mahmudizad">Mehrdad Mahmudizad</a>, <a href="https://publications.waset.org/abstracts/search?q=Roya%20Ahmadi%20Ahangar"> Roya Ahmadi Ahangar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=load%20frequency%20control" title="load frequency control">load frequency control</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy-pid%20controller" title=" fuzzy-pid controller"> fuzzy-pid controller</a>, <a href="https://publications.waset.org/abstracts/search?q=type%202%20fuzzy%20system" title=" type 2 fuzzy system"> type 2 fuzzy system</a>, <a href="https://publications.waset.org/abstracts/search?q=harmony%20search%20algorithm" title=" harmony search algorithm"> harmony search algorithm</a> </p> <a href="https://publications.waset.org/abstracts/52340/improving-load-frequency-control-of-multi-area-power-system-by-considering-uncertainty-by-using-optimized-type-2-fuzzy-pid-controller-with-the-harmony-search-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52340.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">278</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">14961</span> Probability Fuzzy Aggregation Operators in Vehicle Routing Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anna%20Sikharulidze">Anna Sikharulidze</a>, <a href="https://publications.waset.org/abstracts/search?q=Gia%20Sirbiladze"> Gia Sirbiladze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For the evaluation of unreliability levels of movement on the closed routes in the vehicle routing problem, the fuzzy operators family is constructed. The interactions between routing factors in extreme conditions on the roads are considered. A multi-criteria decision-making model (MCDM) is constructed. Constructed aggregations are based on the Choquet integral and the associated probability class of a fuzzy measure. Propositions on the correctness of the extension are proved. Connections between the operators and the compositions of dual triangular norms are described. The conjugate connections between the constructed operators are shown. Operators reflect interactions among all the combinations of the factors in the fuzzy MCDM process. Several variants of constructed operators are used in the decision-making problem regarding the assessment of unreliability and possibility levels of movement on closed routes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vehicle%20routing%20problem" title="vehicle routing problem">vehicle routing problem</a>, <a href="https://publications.waset.org/abstracts/search?q=associated%20probabilities%20of%20a%20fuzzy%20measure" title=" associated probabilities of a fuzzy measure"> associated probabilities of a fuzzy measure</a>, <a href="https://publications.waset.org/abstracts/search?q=choquet%20integral" title=" choquet integral"> choquet integral</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20aggregation%20operator" title=" fuzzy aggregation operator"> fuzzy aggregation operator</a> </p> <a href="https://publications.waset.org/abstracts/60841/probability-fuzzy-aggregation-operators-in-vehicle-routing-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60841.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">326</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">14960</span> Behind Fuzzy Regression Approach: An Exploration Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lavinia%20B.%20Dulla">Lavinia B. Dulla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The exploration study of the fuzzy regression approach attempts to present that fuzzy regression can be used as a possible alternative to classical regression. It likewise seeks to assess the differences and characteristics of simple linear regression and fuzzy regression using the width of prediction interval, mean absolute deviation, and variance of residuals. Based on the simple linear regression model, the fuzzy regression approach is worth considering as an alternative to simple linear regression when the sample size is between 10 and 20. As the sample size increases, the fuzzy regression approach is not applicable to use since the assumption regarding large sample size is already operating within the framework of simple linear regression. Nonetheless, it can be suggested for a practical alternative when decisions often have to be made on the basis of small data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression%20approach" title="fuzzy regression approach">fuzzy regression approach</a>, <a href="https://publications.waset.org/abstracts/search?q=minimum%20fuzziness%20criterion" title=" minimum fuzziness criterion"> minimum fuzziness criterion</a>, <a href="https://publications.waset.org/abstracts/search?q=interval%20regression" title=" interval regression"> interval regression</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20interval" title=" prediction interval"> prediction interval</a> </p> <a href="https://publications.waset.org/abstracts/139364/behind-fuzzy-regression-approach-an-exploration-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139364.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">299</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">14959</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">14958</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">14957</span> Application of Interval Valued Picture Fuzzy Set in Medical Diagnosis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Palash%20Dutta">Palash Dutta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> More frequently uncertainties are encountered in medical diagnosis and therefore it is the most important and interesting area of applications of fuzzy set theory. In this present study, an attempt has been made to extend Sanchez’s approach for medical diagnosis via interval valued picture fuzzy sets and exhibit the technique with suitable case studies. In this article, it is observed that a refusal can be expressed in the databases concerning the examined objects. The technique is performing diagnosis on the basis of distance measures and as a result, this approach makes it possible to introduce weights of all symptoms and consequently patient can be diagnosed directly. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20diagnosis" title="medical diagnosis">medical diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertainty" title=" uncertainty"> uncertainty</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=picture%20fuzzy%20set" title=" picture fuzzy set"> picture fuzzy set</a>, <a href="https://publications.waset.org/abstracts/search?q=interval%20valued%20picture%20fuzzy%20set" title=" interval valued picture fuzzy set"> interval valued picture fuzzy set</a> </p> <a href="https://publications.waset.org/abstracts/54935/application-of-interval-valued-picture-fuzzy-set-in-medical-diagnosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54935.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">379</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">14956</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">14955</span> Assessment the Quality of Telecommunication Services by Fuzzy Inferences System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Oktay%20Nusratov">Oktay Nusratov</a>, <a href="https://publications.waset.org/abstracts/search?q=Ramin%20Rzaev"> Ramin Rzaev</a>, <a href="https://publications.waset.org/abstracts/search?q=Aydin%20Goyushov"> Aydin Goyushov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IP-protocol. To implement the main features and functions of the fuzzy control system of quality telecommunication services it is used multilayer feedforward neural network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quality%20of%20communication" title="quality of communication">quality of communication</a>, <a href="https://publications.waset.org/abstracts/search?q=IP-telephony" title=" IP-telephony"> IP-telephony</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=fuzzy%20implication" title=" fuzzy implication"> fuzzy implication</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a> </p> <a href="https://publications.waset.org/abstracts/15543/assessment-the-quality-of-telecommunication-services-by-fuzzy-inferences-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15543.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">468</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">14954</span> Black Box Model and Evolutionary Fuzzy Control Methods of Coupled-Tank System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Yaman">S. Yaman</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Rostami"> S. Rostami </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a black box modeling of the coupled-tank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=function%20tuner%20method%20%28FTM%29" title="function tuner method (FTM)">function tuner method (FTM)</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20modeling" title=" fuzzy modeling"> fuzzy modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20PID%20controller" title=" fuzzy PID controller"> fuzzy PID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm%20%28GA%29" title=" genetic algorithm (GA)"> genetic algorithm (GA)</a> </p> <a href="https://publications.waset.org/abstracts/50508/black-box-model-and-evolutionary-fuzzy-control-methods-of-coupled-tank-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50508.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">309</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">14953</span> Robust H∞ State Feedback Control for Discrete Time T-S Fuzzy Systems Based on Fuzzy Lyapunov Function Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Walied%20Hanora">Walied Hanora</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the problem of robust state feedback H∞ for discrete time nonlinear system represented by Takagi-Sugeno fuzzy systems. Based on fuzzy lyapunov function, the condition ,which is represented in the form of Liner Matrix Inequalities (LMI), guarantees the H∞ performance of the T-S fuzzy system with uncertainties. By comparison with recent literature, this approach will be more relaxed condition. Finally, an example is given to illustrate the proposed result. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20lyapunov%20function" title="fuzzy lyapunov function">fuzzy lyapunov function</a>, <a href="https://publications.waset.org/abstracts/search?q=H%E2%88%9E%20control" title=" H∞ control "> H∞ control </a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20matrix%20inequalities" title=" linear matrix inequalities"> linear matrix inequalities</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20feedback" title=" state feedback"> state feedback</a>, <a href="https://publications.waset.org/abstracts/search?q=T-S%20fuzzy%20systems" title=" T-S fuzzy systems"> T-S fuzzy systems</a> </p> <a href="https://publications.waset.org/abstracts/58045/robust-h-state-feedback-control-for-discrete-time-t-s-fuzzy-systems-based-on-fuzzy-lyapunov-function-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58045.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">288</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">14952</span> Fuzzy Gauge Capability (Cg and Cgk) through Buckley Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Habib%20A.%20Rahmati">Seyed Habib A. Rahmati</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohsen%20Sadegh%20Amalnick"> Mohsen Sadegh Amalnick </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Different terms of the statistical process control (SPC) has sketch in the fuzzy environment. However, measurement system analysis (MSA), as a main branch of the SPC, is rarely investigated in fuzzy area. This procedure assesses the suitability of the data to be used in later stages or decisions of the SPC. Therefore, this research focuses on some important measures of MSA and through a new method introduces the measures in fuzzy environment. In this method, which works based on Buckley approach, imprecision and vagueness nature of the real world measurement are considered simultaneously. To do so, fuzzy version of the gauge capability (Cg and Cgk) are introduced. The method is also explained through example clearly. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=measurement" title="measurement">measurement</a>, <a href="https://publications.waset.org/abstracts/search?q=SPC" title=" SPC"> SPC</a>, <a href="https://publications.waset.org/abstracts/search?q=MSA" title=" MSA"> MSA</a>, <a href="https://publications.waset.org/abstracts/search?q=gauge%20capability%20%28Cg%20and%20Cgk%29" title=" gauge capability (Cg and Cgk)"> gauge capability (Cg and Cgk)</a> </p> <a href="https://publications.waset.org/abstracts/33559/fuzzy-gauge-capability-cg-and-cgk-through-buckley-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33559.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">650</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">14951</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">14950</span> Fuzzy Linear Programming Approach for Determining the Production Amounts in Food Industry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20G%C3%BCney">B. Güney</a>, <a href="https://publications.waset.org/abstracts/search?q=%C3%87.%20Teke"> Ç. Teke</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, rapid and correct decision making is crucial for both people and enterprises. However, uncertainty makes decision-making difficult. Fuzzy logic is used for coping with this situation. Thus, fuzzy linear programming models are developed in order to handle uncertainty in objective function and the constraints. In this study, a problem of a factory in food industry is investigated, required data is obtained and the problem is figured out as a fuzzy linear programming model. The model is solved using Zimmerman approach which is one of the approaches for fuzzy linear programming. As a result, the solution gives the amount of production for each product type in order to gain maximum profit. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=food%20industry" title="food industry">food industry</a>, <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%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20programming" title=" linear programming "> linear programming </a> </p> <a href="https://publications.waset.org/abstracts/27880/fuzzy-linear-programming-approach-for-determining-the-production-amounts-in-food-industry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27880.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">650</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">14949</span> Design of a Fuzzy Luenberger Observer for Fault Nonlinear System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mounir%20Bekaik">Mounir Bekaik</a>, <a href="https://publications.waset.org/abstracts/search?q=Messaoud%20Ramdani"> Messaoud Ramdani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present in this work a new technique of stabilization for fault nonlinear systems. The approach we adopt focus on a fuzzy Luenverger observer. The T-S approximation of the nonlinear observer is based on fuzzy C-Means clustering algorithm to find local linear subsystems. The MOESP identification approach was applied to design an empirical model describing the subsystems state variables. The gain of the observer is given by the minimization of the estimation error through Lyapunov-krasovskii functional and LMI approach. We consider a three tank hydraulic system for an illustrative example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20system" title="nonlinear system">nonlinear system</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy" title=" fuzzy"> fuzzy</a>, <a href="https://publications.waset.org/abstracts/search?q=faults" title=" faults"> faults</a>, <a href="https://publications.waset.org/abstracts/search?q=TS" title=" TS"> TS</a>, <a href="https://publications.waset.org/abstracts/search?q=Lyapunov-Krasovskii" title=" Lyapunov-Krasovskii"> Lyapunov-Krasovskii</a>, <a href="https://publications.waset.org/abstracts/search?q=observer" title=" observer"> observer</a> </p> <a href="https://publications.waset.org/abstracts/47230/design-of-a-fuzzy-luenberger-observer-for-fault-nonlinear-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47230.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">333</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">14948</span> Modelling and Control of Electrohydraulic System Using Fuzzy Logic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hajara%20Abdulkarim%20Aliyu">Hajara Abdulkarim Aliyu</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulbasid%20Ismail%20Isa"> Abdulbasid Ismail Isa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrohydraulic" title="electrohydraulic">electrohydraulic</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=modelling" title=" modelling"> modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=NZ-PID" title=" NZ-PID"> NZ-PID</a> </p> <a href="https://publications.waset.org/abstracts/46295/modelling-and-control-of-electrohydraulic-system-using-fuzzy-logic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46295.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">470</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">14947</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">14946</span> Application of Fuzzy Approach to the Vibration Fault Diagnosis </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jalel%20Khelil">Jalel Khelil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to improve reliability of Gas Turbine machine especially its generator equipment, a fault diagnosis system based on fuzzy approach is proposed. Three various methods namely K-NN (K-nearest neighbors), F-KNN (Fuzzy K-nearest neighbors) and FNM (Fuzzy nearest mean) are adopted to provide the measurement of relative strength of vibration defaults. Both applications consist of two major steps: Feature extraction and default classification. 09 statistical features are extracted from vibration signals. 03 different classes are used in this study which describes vibrations condition: Normal, unbalance defect, and misalignment defect. The use of the fuzzy approaches and the classification results are discussed. Results show that these approaches yield high successful rates of vibration default classification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fault%20diagnosis" title="fault diagnosis">fault diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20classification%20k-nearest%20neighbor" title=" fuzzy classification k-nearest neighbor"> fuzzy classification k-nearest neighbor</a>, <a href="https://publications.waset.org/abstracts/search?q=vibration" title=" vibration "> vibration </a> </p> <a href="https://publications.waset.org/abstracts/3115/application-of-fuzzy-approach-to-the-vibration-fault-diagnosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3115.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">466</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">14945</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">14944</span> Matlab Method for Exclusive-or Nodes in Fuzzy GERT Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Roland%20Lachmayer">Roland Lachmayer</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahtab%20Afsari"> Mahtab Afsari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Research is the cornerstone for advancement of human communities. So that it is one of the indexes for evaluating advancement of countries. Research projects are usually cost and time-consuming and do not end in result in short term. Project scheduling is one of the integral parts of project management. The present article offers a new method by using C# and Matlab software to solve Fuzzy GERT networks for Exclusive-OR kind of nodes to schedule the network. In this article we concentrate on flowcharts that we used in Matlab to show how we apply Matlab to schedule Exclusive-OR nodes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=research%20projects" title="research projects">research projects</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20GERT" title=" fuzzy GERT"> fuzzy GERT</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20CPM" title=" fuzzy CPM"> fuzzy CPM</a>, <a href="https://publications.waset.org/abstracts/search?q=CPM" title=" CPM"> CPM</a>, <a href="https://publications.waset.org/abstracts/search?q=%CE%B1-cuts" title=" α-cuts"> α-cuts</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a> </p> <a href="https://publications.waset.org/abstracts/16374/matlab-method-for-exclusive-or-nodes-in-fuzzy-gert-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16374.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">398</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">14943</span> H∞ Takagi-Sugeno Fuzzy State-Derivative Feedback Control Design for Nonlinear Dynamic Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Kaewpraek">N. Kaewpraek</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20Assawinchaichote"> W. Assawinchaichote </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper considers an <em>H</em><sub>∞</sub> TS fuzzy state-derivative feedback controller for a class of nonlinear dynamical systems. A Takagi-Sugeno (TS) fuzzy model is used to approximate a class of nonlinear dynamical systems. Then, based on a linear matrix inequality (LMI) approach, we design an <em>H</em><sub>∞ </sub>TS fuzzy state-derivative feedback control law which guarantees <em>L</em><sub>2</sub>-gain of the mapping from the exogenous input noise to the regulated output to be less or equal to a prescribed value. We derive a sufficient condition such that the system with the fuzzy controller is asymptotically stable and <em>H</em><sub>∞</sub> performance is satisfied. Finally, we provide and simulate a numerical example is provided to illustrate the stability and the effectiveness of the proposed controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=h-infinity%20fuzzy%20control" title="h-infinity fuzzy control">h-infinity fuzzy control</a>, <a href="https://publications.waset.org/abstracts/search?q=an%20LMI%20approach" title=" an LMI approach"> an LMI approach</a>, <a href="https://publications.waset.org/abstracts/search?q=Takagi-Sugano%20%28TS%29%20fuzzy%20system" title=" Takagi-Sugano (TS) fuzzy system"> Takagi-Sugano (TS) fuzzy system</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20photovoltaic%20systems" title=" the photovoltaic systems"> the photovoltaic systems</a> </p> <a href="https://publications.waset.org/abstracts/37998/h-takagi-sugeno-fuzzy-state-derivative-feedback-control-design-for-nonlinear-dynamic-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37998.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">384</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">14942</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">14941</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">14940</span> Multi-Criteria Evaluation for the Selection Process of a Wind Power Plant's Location Using Choquet Integral</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Serhat%20T%C3%BCz%C3%BCn">Serhat Tüzün</a>, <a href="https://publications.waset.org/abstracts/search?q=Tufan%20Demirel"> Tufan Demirel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on. <p class="card-text"><strong>Keywords:</strong> <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=choquet%20integral" title=" choquet integral"> choquet integral</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=location%20of%20a%20wind%20power%20plant" title=" location of a wind power plant"> location of a wind power plant</a> </p> <a href="https://publications.waset.org/abstracts/66874/multi-criteria-evaluation-for-the-selection-process-of-a-wind-power-plants-location-using-choquet-integral" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66874.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">412</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">14939</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">14938</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">539</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">14937</span> Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Gherbi">S. Gherbi</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Bouchareb"> F. Bouchareb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=delayed%20systems" title="delayed systems">delayed systems</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20immune%20PID" title=" fuzzy immune PID"> fuzzy immune PID</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Smith%20predictor" title=" Smith predictor"> Smith predictor</a> </p> <a href="https://publications.waset.org/abstracts/10235/optimal-tuning-of-a-fuzzy-immune-pid-parameters-to-control-a-delayed-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10235.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span 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