Fuzzy Logical Algebras and Their Applications
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Data Envelopment Analysis with Fuzzy Parameters: an Interactive Approach
International Journal of Operations Research and Information Systems, 2(3), 39-53, July-September 2011 39 Data Envelopment Analysis with Fuzzy Parameters: An Interactive Approach Adel Hatami-Marbini, Universite Catholique de Louvain, Belgium Saber Saati, Islamic Azad University, Iran Madjid Tavana, La Salle University, USA ABSTRACT Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of deci- sion making units (DMUs) that use multiple inputs to produce multiple outputs. In the conventional DEA, all the data assume the form of specific numerical values. However, the observed values of the input and output data in real-life problems are sometimes imprecise or vague. Previous methods have not considered the preferences of the decision makers (DMs) in the evaluation process. This paper proposes an interactive evaluation process for measuring the relative efficiencies of a set of DMUs in fuzzy DEA with consideration of the DMs’ preferences. The authors construct a linear programming (LP) model with fuzzy parameters and calculate the fuzzy efficiency of the DMUs for different α levels. Then, the DM identifies his or her most preferred fuzzy goal for each DMU under consideration. A modified Yager index is used to develop a ranking order of the DMUs. This study allows the DMs to use their preferences or value judgments when evaluating the performance of the DMUs. Keywords: Data Envelopment Analysis, Efficiency Evaluation, Fuzzy Mathematical Programming, Interactive Solution, Preference Modeling INTRODUCTION efficiency. A DMU is considered efficient when no other DMU can produce more outputs using The changing economic conditions have chal- an equal or lesser amount of inputs. -
Fuzzy Integer Linear Programming with Fuzzy Decision Variables
Applied Mathematical Sciences, Vol. 4, 2010, no. 70, 3493 - 3502 Fuzzy Integer Linear Programming with Fuzzy Decision Variables C. Sudhagar1 Department of Mathematics and Applied Sciences Middle East College of Information Technology, Muscat, Oman [email protected] K. Ganesan Department of Mathematics, SRM University, Chennai, India gansan [email protected] Abstract In this paper a new method for dealing with Fuzzy Integer Linear Programming Problems (FILPP) has been proposed. FILPP with fuzzy variables model was taken for solution. This solution method is based on the fuzzy ranking method. The proposed method can serve deci- sion makers by providing the reasonable range of values for the fuzzy variable, which is comparatively better than the currently available solu- tions. Numerical examples demonstrate the effectiveness and accuracy of the proposed method. Mathematics Subject Classification: 65K05, 90C10, 90C70, 90C90 Keywords: Fuzzy numbers, Ranking, Fuzzy integer linear programming 1 Introduction Linear Programming Problems(LPP) have an outstanding relevance in the field of Decision making, Artificial intelligence, Control theory, Management sciences, Job placement interventions etc. In many practical applications the available information in the system under consideration are not precise. In such situations, it is more appropriate to use the fuzzy LPP. 1Corresponding author 3494 C. Sudhagar and K. Ganesan The concept of fuzzy linear programming problems was first introduced by Tanaka et al.,[13, 12] After his work, several kinds of fuzzy linear programming problems have appeared in the literature and different methods have been proposed to solve such problems. Numerous methods for comparison of fuzzy numbers have been suggested in the literature. In Campos Verdegay paper[2] linear programming problems with fuzzy constraints and fuzzy coefficients in both matrix and right hand side of the constraint set are considered. -
Connes on the Role of Hyperreals in Mathematics
Found Sci DOI 10.1007/s10699-012-9316-5 Tools, Objects, and Chimeras: Connes on the Role of Hyperreals in Mathematics Vladimir Kanovei · Mikhail G. Katz · Thomas Mormann © Springer Science+Business Media Dordrecht 2012 Abstract We examine some of Connes’ criticisms of Robinson’s infinitesimals starting in 1995. Connes sought to exploit the Solovay model S as ammunition against non-standard analysis, but the model tends to boomerang, undercutting Connes’ own earlier work in func- tional analysis. Connes described the hyperreals as both a “virtual theory” and a “chimera”, yet acknowledged that his argument relies on the transfer principle. We analyze Connes’ “dart-throwing” thought experiment, but reach an opposite conclusion. In S, all definable sets of reals are Lebesgue measurable, suggesting that Connes views a theory as being “vir- tual” if it is not definable in a suitable model of ZFC. If so, Connes’ claim that a theory of the hyperreals is “virtual” is refuted by the existence of a definable model of the hyperreal field due to Kanovei and Shelah. Free ultrafilters aren’t definable, yet Connes exploited such ultrafilters both in his own earlier work on the classification of factors in the 1970s and 80s, and in Noncommutative Geometry, raising the question whether the latter may not be vulnera- ble to Connes’ criticism of virtuality. We analyze the philosophical underpinnings of Connes’ argument based on Gödel’s incompleteness theorem, and detect an apparent circularity in Connes’ logic. We document the reliance on non-constructive foundational material, and specifically on the Dixmier trace − (featured on the front cover of Connes’ magnum opus) V. -
The Orthogonality Between Complex Fuzzy Sets and Its Application to Signal Detection
Article The Orthogonality between Complex Fuzzy Sets and Its Application to Signal Detection Bo Hu 1 ID , Lvqing Bi 2 and Songsong Dai 3,* ID 1 School of Mechanical and Electrical Engineering, Guizhou Normal University, Guiyang 550025, China; [email protected] 2 School of Electronics and Communication Engineering, Yulin Normal University, Yulin 537000, China; [email protected] 3 School of Information Science and Engineering, Xiamen University, Xiamen 361005, China * Correspondence: [email protected]; Tel.: +86-592-258-0135 Academic Editor: Hsien-Chung Wu Received: 25 July 2017; Accepted: 25 August 2017; Published: 31 August 2017 Abstract: A complex fuzzy set is a set whose membership values are vectors in the unit circle in the complex plane. This paper establishes the orthogonality relation of complex fuzzy sets. Two complex fuzzy sets are said to be orthogonal if their membership vectors are perpendicular. We present the basic properties of orthogonality of complex fuzzy sets and various results on orthogonality with respect to complex fuzzy complement, complex fuzzy union, complex fuzzy intersection, and complex fuzzy inference methods. Finally, an example application of signal detection demonstrates the utility of the orthogonality of complex fuzzy sets. Keywords: orthogonality; complex fuzzy sets; complex fuzzy operations; complex fuzzy inference 1. Introduction Complex fuzzy sets [1] are an important extension of fuzzy set theory. In recent years, complex fuzzy sets have been successfully used in complex fuzzy inference systems for various applications, such as time series prediction [2–8], function approximation [9–11], and image restoration [12,13]. A complex fuzzy set A on a universe of discourse U is a mapping from U to the unit disc in the complex plane. -
Zerohack Zer0pwn Youranonnews Yevgeniy Anikin Yes Men
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Decision Analysis in the UK Energy Supply Chain Risk Management: Tools Development and Application
Decision Analysis in the UK Energy Supply Chain Risk Management: Tools Development and Application by Amin Vafadarnikjoo Registration number: 100166891 Thesis submitted to The University of East Anglia for the Degree of Doctor of Philosophy (PhD) August 2020 Norwich Business School “This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and that use of any information derived therefrom must be in accordance with current UK Copyright Law. In addition, any quotation or extract must include full attribution.” 1 Abstract Large infrastructures like electricity supply networks are widely presumed to be crucial for the functioning of societies as they create conditions for essential economic activities. There has always been a continuing concern and complexity around risks in the field of energy security and particularly power grids within energy supply chain. Drawing on this complexity and a need for useful tools, this research contributes to developing and utilising proper decision-making tools (i.e. methods and models) to deal with the risk identification and mitigation in the UK energy supply chain as a compound networked system. This thesis is comprised of four study phases (Figure I.A.). It is aimed at developing decision-making tools for risk identification, risk interdependency analysis, risk prioritisation, and long-term risk mitigation strategy recommendations. The application of the tools has focused on the UK power supply chain. The five new tools which are introduced and applied in this thesis are: (1) Proposed Expert Selection Model (ESM) and its application under hesitant fuzzy environment (i.e. -
Fuzzy Relational Maps and Neutrosophic Relational Maps
University of New Mexico UNM Digital Repository Faculty and Staff Publications Mathematics 2004 FUZZY RELATIONAL MAPS AND NEUTROSOPHIC RELATIONAL MAPS Florentin Smarandache University of New Mexico, [email protected] W.B. Vasantha Kandasamy [email protected] Follow this and additional works at: https://digitalrepository.unm.edu/math_fsp Part of the Algebraic Geometry Commons, Analysis Commons, and the Set Theory Commons Recommended Citation W.B. Vasantha Kandasamy & F. Smarandache. FUZZY RELATIONAL MAPS AND NEUTROSOPHIC RELATIONAL MAPS. Church Rock: Hexis, 2004. This Book is brought to you for free and open access by the Mathematics at UNM Digital Repository. It has been accepted for inclusion in Faculty and Staff Publications by an authorized administrator of UNM Digital Repository. For more information, please contact [email protected], [email protected], [email protected]. W. B. VASANTHA KANDASAMY FLORENTIN SMARANDACHE FUZZY RELATIONAL MAPS AND NEUTROSOPHIC RELATIONAL MAPS HEXIS Church Rock 2004 FUZZY RELATIONAL MAPS AND NEUTROSOPHIC RELATIONAL MAPS W. B. Vasantha Kandasamy Department of Mathematics Indian Institute of Technology, Madras Chennai – 600036, India e-mail: [email protected] web: http://mat.iitm.ac.in/~wbv Florentin Smarandache Department of Mathematics University of New Mexico Gallup, NM 87301, USA e-mail: [email protected] HEXIS Church Rock 2004 1 This book can be ordered in a paper bound reprint from: Books on Demand ProQuest Information & Learning (University of Microfilm International) 300 N. Zeeb Road P.O. Box 1346, Ann Arbor MI 48106-1346, USA Tel.: 1-800-521-0600 (Customer Service) http://wwwlib.umi.com/bod/ and online from: Publishing Online, Co. -
Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic
NASA Conference Publication 10111 Proceedings of the Third - _ International Workshop on Neural Networks and T_ Fuzzy Logic , k ('_ASA-CP-1OIII-Vol-2) PRQCEEOINGS N93-22206 i]F ThE TH[_O INTERNATIONAL WORKSHOP --THRU-- ON NEURAL NETWORKS AND FUZZY LOGIC, N93-22223 V_LU_E 2 (NASA) i83 p Unclas Volume II G3/63 0150400 a workshop held at ,nson Space Center Houston, Texas June 1 - 3, 1992 p_ _q_r NASA Conference Publication 10111 Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic Volume II Christopher J. Culbert, Editor NASA Lyndon B. Johnson Space Center Houston, Texas Proceedings of a workshop held at Lyndon B. Johnson Space Center Houston, Texas June 1 - 3, 1992 National Aeronautics and Space Administration January 1993 THIRD INTERNATIONAL WORKSHOP ON NEURAL NETWORKS AND FUZZY LOGIC Program Schedule Monday June 1, 1992 7:30-8:00 Registration 8:00-8:30 Robed T. Savely, Chief Scientist, Information Systems Directorate, NASA/Lyndon B. Johnson Space Center, Houston, TX. Welcoming Remarks. 8:30-9:30 Jon Erickson, Chief Scientist, Automation and Robotics Division, NASNLyndon B. Johnson Space Center, Houston, TX. Space Exploration Needs for Supervised Intelligent Systems. 9:30-9:45 Break Plenary Speakers 9:45-10:30 Piero P. Bonnisone, General Electric, Fuzzy Logic Controllers: A Knowledge-Based Systems Perspective. 10:30-11:15 Robed Farber, Los Alamos National Laboratory, Efficiently Modeling Neural Networks on Massively Parallel Computers. 11:15-1:00 Lunch pRLI_EOING P.._SE BLANK NOT RLMIED iii. w 1:00-1:30 Lawrence O. Hall and Steve G. Romaniuk, University of South Florida, Learning Fuzzy Information in a Hybrid Connectionist, Symbolic Model. -
Global Journal of Science Frontier Research: F Mathematics & Decision Sciences
Online ISSN : 2249-4626 Print ISSN : 0975-5896 DOI : 10.17406/GJSFR SolvingGraphFunctionProblem ModulestotheApplicationAreas FuzzyNumbersDescriptorSystems CliffordianHamiltonianFormulation VOLUME20ISSUE1VERSION1.0 Global Journal of Science Frontier Research: F Mathematics & Decision Sciences Global Journal of Science Frontier Research: F Mathematics & Decision Sciences Volume 20 Issue 1 (Ver. 1.0) Open Association of Research Society Global Journals Inc. © Global Journal of Science (A Delaware USA Incorporation with “Good Standing”; Reg. Number: 0423089) Frontier Research. 2020 . Sponsors:Open Association of Research Society Open Scientific Standards All rights reserved. This is a special issue published in version 1.0 Publisher’s Headquarters office of “Global Journal of Science Frontier Research.” By Global Journals Inc. Global Journals ® Headquarters All articles are open access articles distributed 945th Concord Streets, under “Global Journal of Science Frontier Research” Framingham Massachusetts Pin: 01701, Reading License, which permits restricted use. United States of America Entire contents are copyright by of “Global USA Toll Free: +001-888-839-7392 Journal of Science Frontier Research” unless USA Toll Free Fax: +001-888-839-7392 otherwise noted on specific articles. No part of this publication may be reproduced Offset Typesetting or transmitted in any form or by any means, electronic or mechanical, including G lobal Journals Incorporated photocopy, recording, or any information storage and retrieval system, without written 2nd, Lansdowne, Lansdowne Rd., Croydon-Surrey, permission. Pin: CR9 2ER, United Kingdom The opinions and statements made in this book are those of the authors concerned. Packaging & Continental Dispatching Ultraculture has not verified and neither confirms nor denies any of the foregoing and no warranty or fitness is implied. -
Fuzzy Sets, Fuzzy Logic and Their Applications • Michael Gr
Fuzzy Sets, Fuzzy Logic and Their Applications • Michael Gr. Voskoglou • Michael Gr. Fuzzy Sets, Fuzzy Logic and Their Applications Edited by Michael Gr. Voskoglou Printed Edition of the Special Issue Published in Mathematics www.mdpi.com/journal/mathematics Fuzzy Sets, Fuzzy Logic and Their Applications Fuzzy Sets, Fuzzy Logic and Their Applications Special Issue Editor Michael Gr. Voskoglou MDPI • Basel • Beijing • Wuhan • Barcelona • Belgrade • Manchester • Tokyo • Cluj • Tianjin Special Issue Editor Michael Gr. Voskoglou Graduate Technological Educational Institute of Western Greece Greece Editorial Office MDPI St. Alban-Anlage 66 4052 Basel, Switzerland This is a reprint of articles from the Special Issue published online in the open access journal Mathematics (ISSN 2227-7390) (available at: https://www.mdpi.com/journal/mathematics/special issues/Fuzzy Sets). For citation purposes, cite each article independently as indicated on the article page online and as indicated below: LastName, A.A.; LastName, B.B.; LastName, C.C. Article Title. Journal Name Year, Article Number, Page Range. ISBN 978-3-03928-520-4 (Pbk) ISBN 978-3-03928-521-1 (PDF) c 2020 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons license CC BY-NC-ND. Contents About the Special Issue Editor ...................................... vii Preface to ”Fuzzy Sets, Fuzzy Logic and Their Applications” ................... -
Innovative Uses of Matrices
University of New Mexico UNM Digital Repository Faculty and Staff Publications Mathematics 2012 Innovative Uses of Matrices Florentin Smarandache University of New Mexico, [email protected] W.B. Vasantha Kandasamy [email protected] Indra Venkatbabu Follow this and additional works at: https://digitalrepository.unm.edu/math_fsp Part of the Algebra Commons, Algebraic Geometry Commons, Analysis Commons, Applied Mathematics Commons, Discrete Mathematics and Combinatorics Commons, and the Other Mathematics Commons Recommended Citation W.B. Vasantha Kandasamy, F. Smarandache, I. Venkatbabu. Innovative Uses of Matrices. Ohio: Educational Publisher Inc., 2012. This Book is brought to you for free and open access by the Mathematics at UNM Digital Repository. It has been accepted for inclusion in Faculty and Staff Publications by an authorized administrator of UNM Digital Repository. For more information, please contact [email protected], [email protected], [email protected]. Innovative Uses of Matrices W. B. Vasantha Kandasamy Florentin Smarandache Indra Venkatbabu Educational Publisher Inc. Ohio 2012 This book can be ordered from: Education Publisher Inc. 1313 Chesapeake Ave. Columbus, Ohio 43212, USA Toll Free: 1-866-880-5373 Copyright 2012 by Educational Publisher Inc. and the Authors Peer reviewers: Professor Paul P. Wang, Ph D, Department of Electrical & Computer Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA Prof. Catalin Barbu, V. Alecsandri National College, Mathematics Department, Bacau, Romania -
TME Volume 7, Number 1
The Mathematics Enthusiast Volume 7 Number 1 Article 10 1-2010 TME Volume 7, Number 1 Follow this and additional works at: https://scholarworks.umt.edu/tme Part of the Mathematics Commons Let us know how access to this document benefits ou.y Recommended Citation (2010) "TME Volume 7, Number 1," The Mathematics Enthusiast: Vol. 7 : No. 1 , Article 10. Available at: https://scholarworks.umt.edu/tme/vol7/iss1/10 This Full Volume is brought to you for free and open access by ScholarWorks at University of Montana. It has been accepted for inclusion in The Mathematics Enthusiast by an authorized editor of ScholarWorks at University of Montana. For more information, please contact [email protected]. The Montana Mathematics Enthusiast ISSN 1551-3440 VOL. 7, NO.1, January 2010, pp.1-174 Editor-in-Chief Bharath Sriraman, The University of Montana Associate Editors: Lyn D. English, Queensland University of Technology, Australia Simon Goodchild, University of Agder, Norway Brian Greer, Portland State University, USA Luis Moreno-Armella, Cinvestav-IPN, México International Editorial Advisory Board Mehdi Alaeiyan, Iran University of Science and Technology, Iran Miriam Amit, Ben-Gurion University of the Negev, Israel Ziya Argun, Gazi University, Turkey Ahmet Arikan, Gazi University, Turkey. Astrid Beckmann, University of Education, Schwäbisch Gmünd, Germany Raymond Bjuland, University of Stavanger, Norway Morten Blomhøj, Roskilde University, Denmark Robert Carson, Montana State University- Bozeman, USA Mohan Chinnappan, University of Wollongong,