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set</title> <meta name="description" content="Search results for: fuzzy set"> <meta name="keywords" content="fuzzy 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 Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" 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style="font-size:.9rem"><span class="badge badge-info">709</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">708</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">707</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">706</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">705</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">704</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">703</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">702</span> A Fuzzy Nonlinear Regression Model for Interval Type-2 Fuzzy Sets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20Poleshchuk">O. Poleshchuk</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Komarov"> E. Komarov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=interval%20type-2%20fuzzy%20sets" title="interval type-2 fuzzy sets">interval type-2 fuzzy sets</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression" title=" fuzzy regression"> fuzzy regression</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20interval" title=" weighted interval"> weighted interval</a> </p> <a href="https://publications.waset.org/abstracts/6138/a-fuzzy-nonlinear-regression-model-for-interval-type-2-fuzzy-sets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6138.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">373</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">701</span> A Fuzzy Mathematical Model for Order Acceptance and Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=E.%20Koyuncu">E. Koyuncu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20mathematical%20programming" title="fuzzy mathematical programming">fuzzy mathematical programming</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20ranking" title=" fuzzy ranking"> fuzzy ranking</a>, <a href="https://publications.waset.org/abstracts/search?q=order%20acceptance" title=" order acceptance"> order acceptance</a>, <a href="https://publications.waset.org/abstracts/search?q=single%20machine%20scheduling" title=" single machine scheduling"> single machine scheduling</a> </p> <a href="https://publications.waset.org/abstracts/62385/a-fuzzy-mathematical-model-for-order-acceptance-and-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62385.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">338</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">700</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">699</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">698</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">697</span> A Fuzzy Kernel K-Medoids Algorithm for Clustering Uncertain Data Objects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Behnam%20Tavakkol">Behnam Tavakkol</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Uncertain data mining algorithms use different ways to consider uncertainty in data such as by representing a data object as a sample of points or a probability distribution. Fuzzy methods have long been used for clustering traditional (certain) data objects. They are used to produce non-crisp cluster labels. For uncertain data, however, besides some uncertain fuzzy k-medoids algorithms, not many other fuzzy clustering methods have been developed. In this work, we develop a fuzzy kernel k-medoids algorithm for clustering uncertain data objects. The developed fuzzy kernel k-medoids algorithm is superior to existing fuzzy k-medoids algorithms in clustering data sets with non-linearly separable clusters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clustering%20algorithm" title="clustering algorithm">clustering algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20methods" title=" fuzzy methods"> fuzzy methods</a>, <a href="https://publications.waset.org/abstracts/search?q=kernel%20k-medoids" title=" kernel k-medoids"> kernel k-medoids</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertain%20data" title=" uncertain data"> uncertain data</a> </p> <a href="https://publications.waset.org/abstracts/123501/a-fuzzy-kernel-k-medoids-algorithm-for-clustering-uncertain-data-objects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/123501.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">215</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">696</span> Derivation of BCK\BCI-Algebras</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tumadhir%20Fahim%20M%20Alsulami">Tumadhir Fahim M Alsulami</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The concept of this paper builds on connecting between two important notions, fuzzy ideals of BCK-algebras and derivation of BCI-algebras. The result we got is a new concept called derivation fuzzy ideals of BCI-algebras. Followed by various results and important theorems on different types of ideals. In chapter 1: We presented the basic and fundamental concepts of BCK\ BCI- algebras as follows: BCK/BCI-algebras, BCK sub-algebras, bounded BCK-algebras, positive implicative BCK-algebras, commutative BCK-algebras, implicative BCK- algebras. Moreover, we discussed ideals of BCK-algebras, positive implicative ideals, implicative ideals and commutative ideals. In the last section of chapter 1 we proposed the notion of derivation of BCI-algebras, regular derivation of BCI-algebras and basic definitions and properties. In chapter 2: It includes 3 sections as follows: Section 1 contains elementary concepts of fuzzy sets and fuzzy set operations. Section 2 shows O. G. Xi idea, where he applies fuzzy sets concept to BCK-algebras and we studied fuzzy sub-algebras as well. Section 3 contains fuzzy ideals of BCK-algebras basic definitions, closed fuzzy ideals, fuzzy commutative ideals, fuzzy positive implicative ideals, fuzzy implicative ideals, fuzzy H-ideals and fuzzy p-ideals. Moreover, we investigated their concepts in diverse theorems and propositions. In chapter 3: The main concept of our thesis on derivation fuzzy ideals of BCI- algebras is introduced. Chapter 3 splits into 4 sections. We start with General definitions and important theorems on derivation fuzzy ideal theory in section 1. Section 2 and 3 contain derivations fuzzy p-ideals and derivations fuzzy H-ideals of BCI- algebras, several important theorems and propositions were introduced. The last section studied derivations fuzzy implicative ideals of BCI-algebras and it includes new theorems and results. Furthermore, we presented a new theorem that associate derivations fuzzy implicative ideals, derivations fuzzy positive implicative ideals and derivations fuzzy commutative ideals. These concepts and the new results were obtained and introduced in chapter 3 were submitted in two separated articles and accepted for publication. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BCK" title="BCK">BCK</a>, <a href="https://publications.waset.org/abstracts/search?q=BCI" title=" BCI"> BCI</a>, <a href="https://publications.waset.org/abstracts/search?q=algebras" title=" algebras"> algebras</a>, <a href="https://publications.waset.org/abstracts/search?q=derivation" title=" derivation"> derivation</a> </p> <a href="https://publications.waset.org/abstracts/148017/derivation-of-bckbci-algebras" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148017.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">124</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">695</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">378</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">694</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">693</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">692</span> A Different Approach to Optimize Fuzzy Membership Functions with Extended FIR Filter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jun-Ho%20Chung">Jun-Ho Chung</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Hyun%20Yoo"> Sung-Hyun Yoo</a>, <a href="https://publications.waset.org/abstracts/search?q=In-Hwan%20Choi"> In-Hwan Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hyun-Kook%20Lee"> Hyun-Kook Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Moon-Kyu%20Song"> Moon-Kyu Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Choon-Ki%20Ahn"> Choon-Ki Ahn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The extended finite impulse response (EFIR) filter is addressed to optimize membership functions (MFs) of the fuzzy model that has strong nonlinearity. MFs are important parts of the fuzzy logic system (FLS) and, thus optimizing MFs of FLS is one of approaches to improve the performance of output. We employ the EFIR as an alternative optimization option to nonlinear fuzzy model. The performance of EFIR is demonstrated on a fuzzy cruise control via a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20system" title="fuzzy logic system">fuzzy logic system</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=extended%20FIR%20filter" title=" extended FIR filter"> extended FIR filter</a> </p> <a href="https://publications.waset.org/abstracts/42104/a-different-approach-to-optimize-fuzzy-membership-functions-with-extended-fir-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42104.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">723</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">691</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">287</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">690</span> Fuzzy Inference System for Diagnosis of Malaria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Purnima%20Pandit">Purnima Pandit</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Malaria remains one of the world’s most deadly infectious disease and arguably, the greatest menace to modern society in terms of morbidity and mortality. To choose the right treatment and to ensure a quality of life suitable for a specific patient condition, early and accurate diagnosis of malaria is essential. It reduces transmission of disease and prevents deaths. Our work focuses on designing an efficient, accurate fuzzy inference system for malaria diagnosis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20inference%20system" title="fuzzy inference system">fuzzy inference system</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=malaria%20disease" title=" malaria disease"> malaria disease</a>, <a href="https://publications.waset.org/abstracts/search?q=triangular%20fuzzy%20number" title=" triangular fuzzy number"> triangular fuzzy number</a> </p> <a href="https://publications.waset.org/abstracts/55107/fuzzy-inference-system-for-diagnosis-of-malaria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55107.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">689</span> Caputo-Type Fuzzy Fractional Riccati Differential Equations with Fuzzy Initial Conditions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Trilok%20Mathur">Trilok Mathur</a>, <a href="https://publications.waset.org/abstracts/search?q=Shivi%20Agarwal"> Shivi Agarwal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with the solutions of fuzzy-fractional-order Riccati equations under Caputo-type fuzzy fractional derivatives. The Caputo-type fuzzy fractional derivatives are defined based on Hukuhura difference and strongly generalized fuzzy differentiability. The Laplace-Adomian-Pade method is used for solving fractional Riccati-type initial value differential equations of fractional order. Moreover, we also displayed some examples to illustrate our methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Caputo-type%20fuzzy%20fractional%20derivative" title="Caputo-type fuzzy fractional derivative">Caputo-type fuzzy fractional derivative</a>, <a href="https://publications.waset.org/abstracts/search?q=Fractional%20Riccati%20differential%20equations" title=" Fractional Riccati differential equations"> Fractional Riccati differential equations</a>, <a href="https://publications.waset.org/abstracts/search?q=Laplace-Adomian-Pade%20method" title=" Laplace-Adomian-Pade method"> Laplace-Adomian-Pade method</a>, <a href="https://publications.waset.org/abstracts/search?q=Mittag%20Leffler%20function" title=" Mittag Leffler function"> Mittag Leffler function</a> </p> <a href="https://publications.waset.org/abstracts/51080/caputo-type-fuzzy-fractional-riccati-differential-equations-with-fuzzy-initial-conditions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51080.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">395</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">688</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">687</span> The Analysis of Different Classes of Weighted Fuzzy Petri Nets and Their Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yurii%20Bloshko">Yurii Bloshko</a>, <a href="https://publications.waset.org/abstracts/search?q=Oksana%20Olar"> Oksana Olar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the analysis of 6 different classes of Petri nets: fuzzy Petri nets (FPN), generalized fuzzy Petri nets (GFPN), parameterized fuzzy Petri nets (PFPN), T2GFPN, flexible generalized fuzzy Petri nets (FGFPN), binary Petri nets (BPN). These classes were simulated in the special software PNeS® for the analysis of its pros and cons on the example of models which are dedicated to the decision-making process of passenger transport logistics. The paper includes the analysis of two approaches: when input values are filled with the experts’ knowledge; when fuzzy expectations represented by output values are added to the point. These approaches fulfill the possibilities of triples of functions which are replaced with different combinations of t-/s-norms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20petri%20net" title="fuzzy petri net">fuzzy petri net</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20computational%20techniques" title=" intelligent computational techniques"> intelligent computational techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20representation" title=" knowledge representation"> knowledge representation</a>, <a href="https://publications.waset.org/abstracts/search?q=triangular%20norms" title=" triangular norms"> triangular norms</a> </p> <a href="https://publications.waset.org/abstracts/147433/the-analysis-of-different-classes-of-weighted-fuzzy-petri-nets-and-their-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147433.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">141</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">686</span> General Network with Four Nodes and Four Activities with Triangular Fuzzy Number as Activity Times</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashmi%20Tamhankar">Rashmi Tamhankar</a>, <a href="https://publications.waset.org/abstracts/search?q=Madhav%20Bapat"> Madhav Bapat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In many projects, we have to use human judgment for determining the duration of the activities which may vary from person to person. Hence, there is vagueness about the time duration for activities in network planning. Fuzzy sets can handle such vague or imprecise concepts and has an application to such network. The vague activity times can be represented by triangular fuzzy numbers. In this paper, a general network with fuzzy activity times is considered and conditions for the critical path are obtained also we compute total float time of each activity. Several numerical examples are discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PERT" title="PERT">PERT</a>, <a href="https://publications.waset.org/abstracts/search?q=CPM" title=" CPM"> CPM</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%20activity%20times" title=" fuzzy activity times "> fuzzy activity times </a> </p> <a href="https://publications.waset.org/abstracts/28350/general-network-with-four-nodes-and-four-activities-with-triangular-fuzzy-number-as-activity-times" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28350.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">473</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">685</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">298</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">684</span> A New Reliability Allocation Method Based on Fuzzy Numbers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Peng%20Li">Peng Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Chuanri%20Li"> Chuanri Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Tao%20Li"> Tao Li </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Reliability allocation is quite important during early design and development stages for a system to apportion its specified reliability goal to subsystems. This paper improves the reliability fuzzy allocation method and gives concrete processes on determining the factor set, the factor weight set, judgment set, and multi-grade fuzzy comprehensive evaluation. To determine the weight of factor set, the modified trapezoidal numbers are proposed to reduce errors caused by subjective factors. To decrease the fuzziness in the fuzzy division, an approximation method based on linear programming is employed. To compute the explicit values of fuzzy numbers, centroid method of defuzzification is considered. An example is provided to illustrate the application of the proposed reliability allocation method based on fuzzy arithmetic. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reliability%20allocation" title="reliability allocation">reliability allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20arithmetic" title=" fuzzy arithmetic"> fuzzy arithmetic</a>, <a href="https://publications.waset.org/abstracts/search?q=allocation%20weight" title=" allocation weight"> allocation weight</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/27101/a-new-reliability-allocation-method-based-on-fuzzy-numbers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27101.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">342</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">683</span> A Fuzzy Linear Regression Model Based on Dissemblance Index</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shih-Pin%20Chen">Shih-Pin Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Shih-Syuan%20You"> Shih-Syuan You</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy regression models are useful for investigating the relationship between explanatory variables and responses in fuzzy environments. To overcome the deficiencies of previous models and increase the explanatory power of fuzzy data, the graded mean integration (GMI) representation is applied to determine representative crisp regression coefficients. A fuzzy regression model is constructed based on the modified dissemblance index (MDI), which can precisely measure the actual total error. Compared with previous studies based on the proposed MDI and distance criterion, the results from commonly used test examples show that the proposed fuzzy linear regression model has higher explanatory power and forecasting accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dissemblance%20index" title="dissemblance index">dissemblance index</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20linear%20regression" title=" fuzzy linear regression"> fuzzy linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=graded%20mean%20integration" title=" graded mean integration"> graded mean integration</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20programming" title=" mathematical programming"> mathematical programming</a> </p> <a href="https://publications.waset.org/abstracts/9968/a-fuzzy-linear-regression-model-based-on-dissemblance-index" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9968.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">438</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">682</span> Integration of Fuzzy Logic in the Representation of Knowledge: Application in the Building Domain</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hafida%20Bouarfa">Hafida Bouarfa</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Abed"> Mohamed Abed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=case%20based%20reasoning" title="case based reasoning">case based reasoning</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%20case%20based%20reasoning" title=" fuzzy case based reasoning"> fuzzy case based reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=seismic%20vulnerability" title=" seismic vulnerability"> seismic vulnerability</a> </p> <a href="https://publications.waset.org/abstracts/11237/integration-of-fuzzy-logic-in-the-representation-of-knowledge-application-in-the-building-domain" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11237.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">292</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">681</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">680</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> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20set&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20set&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20set&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=fuzzy%20set&page=5">5</a></li> <li class="page-item"><a class="page-link" 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href="https://publications.waset.org/abstracts/search?q=fuzzy%20set&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a 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