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Fuzzy Logic Type 1 and Type 2 Based on LabVIEWTM FPGA
by Pedro Ponce-Cruz Arturo Molina Brian MaccleeryThis book is a comprehensive introduction to LabVIEW FPGA(tm), a package allowing the programming of intelligent digital controllers in field programmable gate arrays (FPGAs) using graphical code. It shows how both potential difficulties with understanding and programming in VHDL and the consequent difficulty and slowness of implementation can be sidestepped. The text includes a clear theoretical explanation of fuzzy logic (type 1 and type 2) with case studies that implement the theory and systematically demonstrate the implementation process. It goes on to describe basic and advanced levels of programming LabVIEW FPGA and show how implementation of fuzzy-logic control in FPGAs improves system responses. A complete toolkit for implementing fuzzy controllers in LabVIEW FPGA has been developed with the book so that readers can generate new fuzzy controllers and deploy them immediately. Problems and their solutions allow readers to practice the techniques and to absorb the theoretical ideas as they arise. Fuzzy Logic Type 1 and Type 2 Based on LabVIEW FPGA(tm), helps students studying embedded control systems to design and program those controllers more efficiently and to understand the benefits of using fuzzy logic in doing so. Researchers working with FPGAs find the text useful as an introduction to LabVIEW and as a tool helping them design embedded systems.
Fuzzy Logic and Applications: 12th International Workshop, Wilf 2018, Genoa, Italy, September 6-7, 2018, Revised Selected Papers (Lecture Notes in Computer Science #11291)
by Francesco Masulli Robert Fullér Silvio GioveThis book constitutes the post-conference proceedings of the 12th International Workshop on Fuzzy Logic and Applications, WILF 2018, held in Genoa, Italy, in September 2018. <P><P> The 17 revised full papers and 9 short papers were carefully reviewed and selected from 26 submissions. The papers are organized in topical sections on fuzzy logic theory, recent applications of fuzzy logic, and fuzzy decision making. Also included are papers from the round table "Zadeh and the future of logic" and a tutorial.
Fuzzy Logic and Information Fusion
by Tomasa Calvo Sánchez Joan Torrens SastreThis book offers a timely report on keytheories and applications of soft-computing. Written in honour of ProfessorGaspar Mayor on his 70th birthday, it primarily focuses on areas related to hisresearch, including fuzzy binary operators, aggregation functions,multi-distances, and fuzzy consensus/decision models. It also discusses anumber of interesting applications such as the implementation of fuzzymathematical morphology based on Mayor-Torrens t-norms. Importantly, thedifferent chapters, authored by leading experts, present novel results andoffer new perspectives on different aspects of Mayor's research. The book alsoincludes an overview of evolutionary fuzzy systems, a topic that is not one of Mayor's main areas of interest, and a final chapterwritten by the Spanish pioneer in fuzzylogic, Professor E. Trillas. Computer and decision scientists, knowledgeengineers and mathematicians alike will find here an authoritative overview ofkey soft-computing concepts and techniques.
Fuzzy Logic and Soft Computing Applications
by Witold Pedrycz Alfredo Petrosino Vincenzo LoiaThis book comprises a selection of papers from the IFSA 2007 World Congress on theoretical advances and applications of fuzzy logic and soft computing. These papers were selected from over 400 submissions and constitute an important contribution to the theory and applications of fuzzy logic and soft computing methodologies. Soft Computing consists of several computing paradigms, including fuzzy logic, neural networks, genetic algorithms, and other techniques, which can be used to produce powerful intelligent systems for solving real-world problems. Applications range from pattern recognition to intelligent control and sow the advantages of using soft computing theory and methods. The papers of IFSA 2007 also make a contribution to this goal.
Fuzzy Logic for Image Processing
by Laura Caponetti Giovanna CastellanoThis book provides an introduction to fuzzy logic approaches useful in image processing. The authors start by introducing image processing tasks of low and medium level such as thresholding, enhancement, edge detection, morphological filters, and segmentation and shows how fuzzy logic approaches apply. The book is divided into two parts. The first includes vagueness and ambiguity in digital images, fuzzy image processing, fuzzy rule based systems, and fuzzy clustering. The second part includes applications to image processing, image thresholding, color contrast enhancement, edge detection, morphological analysis, and image segmentation. Throughout, they describe image processing algorithms based on fuzzy logic under methodological aspects in addition to applicative aspects. Implementations in java are provided for the various applications.
Fuzzy Logic in Intelligent System Design
by Oscar Castillo Patricia Melin Janusz Kacprzyk Marek Reformat William MelekThis book describes recent advances in the use of fuzzy logic for the design of hybrid intelligent systems based on nature-inspired optimization and their applications in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Based on papers presented at the North American Fuzzy Information Processing Society Annual Conference (NAFIPS 2017), held in Cancun, Mexico from 16 to 18 October 2017, the book is divided into nine main parts, the first of which first addresses theoretical aspects, and proposes new concepts and algorithms based on type-1 fuzzy systems. The second part consists of papers on new concepts and algorithms for type-2 fuzzy systems, and on applications of type-2 fuzzy systems in diverse areas, such as time series prediction and pattern recognition. In turn, the third part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques describing new nature-inspired optimization algorithms that use fuzzy dynamic adaptation of parameters. The fourth part presents emergent intelligent models, which range from quantum algorithms to cellular automata. The fifth part explores applications of fuzzy logic in diverse areas of medicine, such as the diagnosis of hypertension and heart diseases. The sixth part describes new computational intelligence algorithms and their applications in different areas of intelligent control, while the seventh examines the use of fuzzy logic in different mathematic models. The eight part deals with a diverse range of applications of fuzzy logic, ranging from environmental to autonomous navigation, while the ninth covers theoretical concepts of fuzzy models
Fuzzy Logic in Its 50th Year
by Cengiz Kahraman Uzay Kaymak Adnan YaziciThis book offers a multifacetedperspective on fuzzy set theory, discussing its developments over the last 50years. It reports on all types of fuzzy sets, from ordinary to hesitant fuzzysets, with each one explained by its own developers, authoritative scientistswell known for their previous works. Highlighting recent theorems and proofs,the book also explores how fuzzy set theory has come to be extensively used inalmost all branches of science, including the health sciences, decisionscience, earth science and the social sciences alike. It presents a wealth ofreal-world sample applications, from routing problem to robotics, and fromagriculture to engineering. By offering a comprehensive, timely and detailedportrait of the field, the book represents an excellent reference guide forresearchers, lecturers and postgraduate students pursuing research on new fuzzyset extensions.
Fuzzy Logic of Quasi-Truth: An Algebraic Treatment
by Antonio Di Nola Revaz Grigolia Esko TurunenThis book presents the first algebraic treatment of quasi-truth fuzzylogic and covers the algebraic foundations of many-valued logic. Itoffers a comprehensive account of basic techniques and reports on importantresults showing the pivotal role played by perfect many-valued algebras(MV-algebras). It is well known that the first-order predicate Łukasiewiczlogic is not complete with respect to the canonical set of truth values. However, it is complete with respect to alllinearly ordered MV -algebras. As there are no simple linearly orderedMV-algebras in this case, infinitesimal elements of an MV-algebra are allowedto be truth values. The book presents perfect algebras as an interestingsubclass of local MV-algebras and provides readers with the necessary knowledgeand tools for formalizing the fuzzy concept of quasi true and quasi false. Allbasic concepts are introduced in detail to promote a better understanding ofthe more complex ones. It is an advanced and inspiring reference-guide forgraduate students and researchers in the field of non-classical many-valuedlogics.
Fuzzy Logic: Recent Applications and Developments
by Jenny Carter Francisco Chiclana Arjab Singh Khuman Tianhua ChenSince its inception, fuzzy logic has attracted an incredible amount of interest, and this interest continues to grow at an exponential rate. As such, scientists, researchers, educators and practitioners of fuzzy logic continue to expand on the applicability of what and how fuzzy can be utilised in the real-world. In this book, the authors present key application areas where fuzzy has had significant success. The chapters cover a plethora of application domains, proving credence to the versatility and robustness of a fuzzy approach. A better understanding of fuzzy will ultimately allow for a better appreciation of fuzzy. This book provides the reader with a varied range of examples to illustrate what fuzzy logic can be capable of and how it can be applied. The text will be ideal for individuals new to the notion of fuzzy, as well as for early career academics who wish to further expand on their knowledge of fuzzy applications. The book is also suitable as a supporting text for advanced undergraduate and graduate-level modules on fuzzy logic, soft computing, and applications of AI.
Fuzzy Mathematics: A Fundamental Introduction (Synthesis Lectures on Mathematics & Statistics)
by Apostolos SyropoulosThis book aims to introduce readers without a strong mathematical background to the basic ideas of fuzzy set theory and logic. Fuzzy mathematics is the mathematics of vagueness, a universal property of this world. There are many objects that are called vague because they cannot be precisely defined. Since vagueness is so common, a tool is needed to describe it and to effectively deal with it. Fuzzy mathematics is such a tool, and it is used by most researchers and scholars. As such, this book provides a short overview of the field written for non-specialists. This book allows readers to delve into the theory of fuzzy sets and introduces core mathematical ideas without using the usual formalities of books in mathematics, i.e. theorems, proofs, etc.
Fuzzy Models in Economics (Studies in Fuzziness and Soft Computing #402)
by Gorkhmaz ImanovThis book offers a timely guide to fuzzy methods applied to the analysis of socioeconomic systems. It provides readers with a comprehensive and up-to-date overview of the algorithms, including the theory behind them, as well as practical considerations, current limitations and solutions. Each chapter focuses on a different economic problem, explaining step by step the process to approach it, using the corresponding fuzzy tools. The book covers elements of intuitionistic fuzzy logics, fuzzy entropy and the fuzzy DEMATEL method, a fuzzy approach to calculate the financial stability index. It also reports on some new models of social, financial and ecological security, and on a novel fuzzy method for evaluating the quality of development of information economy.
Fuzzy Multiple Objective Decision Making
by Gwo-Hshiung Tzeng Jih-Jeng HuangMulti-objective programming (MOP) can simultaneously optimize multi-objectives in mathematical programming models, but the optimization of multi-objectives triggers the issue of Pareto solutions and complicates the derived answers. To address these problems, researchers often incorporate the concepts of fuzzy sets and evolutionary algorithms into M
Fuzzy Operator Theory in Mathematical Analysis
by Reza Saadati Yeol Je Cho Themistocles M. RassiasThis self-contained monograph presents an overview of fuzzy operator theory in mathematical analysis. Concepts, principles, methods, techniques, and applications of fuzzy operator theory are unified in this book to provide an introduction to graduate students and researchers in mathematics, applied sciences, physics, engineering, optimization, and operations research. New approaches to fuzzy operator theory and fixed point theory with applications to fuzzy metric spaces, fuzzy normed spaces, partially ordered fuzzy metric spaces, fuzzy normed algebras, and non-Archimedean fuzzy metric spaces are presented. Surveys are provided on: Basic theory of fuzzy metric and normed spaces and its topology, fuzzy normed and Banach spaces, linear operators, fundamental theorems (open mapping and closed graph), applications of contractions and fixed point theory, approximation theory and best proximity theory, fuzzy metric type space, topology and applications.
Fuzzy Optimization Techniques in the Areas of Science and Management (Computational Intelligence in Engineering Problem Solving)
by Santosh Kumar Das Massimiliano GiacaloneThis book helps to enhance the application of fuzzy logic optimization in the areas of science and engineering. It includes implementation and modeling paradigms such as path planning and routing design for different wireless networks, organization behavior strategies modeling, and so forth. It also: Explains inventory control management, uncertainties management, loss minimization, game optimization, data analysis and prediction, and different decision-making system and management, and so forth. Describes applicability of fuzzy optimization techniques in areas of science and management. Resolves several issues based on uncertainty using member function. Helps to map different problems based on mathematical modelling. Includes issues and problems based on linear and non-linear optimizations. Focuses on management science such as manpower management and inventory planning. This book is aimed at researchers and graduate students in signal processing, power systems, systems and industrial engineering, and computer networks.
Fuzzy Optimization, Decision-making and Operations Research: Theory and Applications
by Madhumangal Pal Chiranjibe Jana Ghulam Muhiuddin Peide LiuAfter developing fuzzy set theory, many contributors focused their research on the extension of fuzzy sets and their computational methodologies, strengthening modern science and technology. In some real-life phenomena, the conventional methods and traditional fuzzy sets cannot be explained, whereas the extension of fuzzy sets and effective new computing methods can explain it adequately. This edited book presents a new view of fuzzy set-measurement methods entitled "Fuzzy Optimization, Decision Making and Operations Research: Theory and Applications", which deals with different perspectives and areas of research. All chapters are divided into three parts: fuzzy optimization, fuzzy decision-making, and fuzzy operation research. The goal of this book is to provide a relevant methodological framework covering the core fields of fuzzy decision-making method, fuzzy optimization method, fuzzy graphics method, fuzzy operations research, fuzzy optimization using graph theory, fuzzy support systems and its real and industrial applications. For many people, fuzzy words' industrial engineering and scientific meanings are still an advanced system for improving modern science and technology. Although fuzzy logic can be applied to many different areas, people do not know how different fuzzy approaches can be applied to various products currently on the market. It is written for professionals who wish to share their expertise, improve their findings, and provide relevant information in the fields of fuzzy methods and their application in decision-making, optimization theory, graph theory and operations research. This book is aimed at experts and practitioners in the fields of fuzzy optimization, fuzzy decision-making, and fuzzy operation research.
Fuzzy Pictures as Philosophical Problem and Scientific Practice
by Jordi CatThis book presents a comprehensive discussion on the characterization of vagueness in pictures. It reports on how the problem of representation of images has been approached in scientific practice, highlighting the role of mathematical methods and the philosophical background relevant for issues such as representation, categorization and reasoning. Without delving too much into the technical details, the book examines and defends different kinds of values of fuzziness based on a complex approach to categorization as a practice, adopting conceptual and empirical suggestions from different fields including the arts. It subsequently advances criticisms and provides suggestions for interpretation and application. By describing a cognitive framework based on fuzzy, rough and near sets, and discussing all of the relevant mathematical and philosophical theories for the representation and processing of vagueness in images, the book offers a practice-oriented guide to fuzzy visual reasoning, along with novel insights into the field of interpreting and thinking with fuzzy pictures and fuzzy data.
Fuzzy Recurrence Plots and Networks with Applications in Biomedicine
by Tuan D. PhamThis book presents an original combination of three well-known methodological approaches for nonlinear data analysis: recurrence, networks, and fuzzy logic.After basic concepts of these three approaches are introduced, this book presents recently developed methods known as fuzzy recurrence plots and fuzzy recurrence networks. Computer programs written in MATLAB, which implement the basic algorithms, are included to facilitate the understanding of the developed ideas. Several applications of these techniques to biomedical problems, ranging from cancer and neurodegenerative disease to depression, are illustrated to show the potential of fuzzy recurrence methods. This book opens a new door to theorists in complex systems science as well as specialists in medicine, biology, engineering, physics, computer science, geosciences, and social economics to address issues in experimental nonlinear signal and data processing.
Fuzzy Sets Theory Preliminary: Can A Washing Machine Think?
by Bing-Yuan Cao Hao-Ran Lin Yun-Zhang LiaoThis basic book has been used at the middle schools in Shanghai, China for more than 10 years. The book presents carefully-selected contents in order to achieve the roles of enlightenment and popularization. It mainly includes: Chapter 1: Human Brains, Computers and Fuzzy Mathematics; Chapter 2: Matrix, Fuzzy Relations and Fuzzy Matrix; Chapter 3: Fuzzy Control; Chapter 4: Fuzzy Statistics and Fuzzy Probability and Chapter 5: Fuzzy Linear Programming. It includes at the end of each chapter concise, interesting and profound reading and thinking materials, and a certain amount of exercises so as to make it an informative and interesting textbook. This book can be used not only as a textbook in senior middle schools, and in vocational colleges, but also as a primer for individually learning fuzzy mathematics.
Fuzzy Sets, Rough Sets, Multisets and Clustering
by Vicenç Torra Yasuo Narukawa Anders DahlbomThis book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.
Fuzzy Sets-Based Methods and Techniques for Modern Analytics (Studies in Fuzziness and Soft Computing #364)
by José Luis Verdegay Ali EbrahimnejadThe book offers a comprehensive, practice-oriented introduction to the field of fuzzy mathematical programming (FMP) as key topic of modern analytics. FMP plays a fundamental role in dealing with a varied range of problems, such as those concerning smart cities, sustainability, and renewable energies. This book includes an introduction to the basic concepts, together with extensive information on the computational-intelligence-based optimization models and techniques that have been used to date. Special emphasis is given to fuzzy transportation problems. The book is a valuable resource for researchers, data scientists and practitioners dealing with computational-intelligence-based optimization models for analytics.
Fuzzy Social Choice Models
by Peter C. Casey Michael B. Gibilisco Carly A. Goodman Kelly Nelson Pook John N. Mordeson Mark J. Wierman Terry D. ClarkThis book explores the extent to which fuzzy set logic can overcome some of the shortcomings of public choice theory, particularly its inability to provide adequate predictive power in empirical studies. Especially in the case of social preferences, public choice theory has failed to produce the set of alternatives from which collective choices are made. The book presents empirical findings achieved by the authors in their efforts to predict the outcome of government formation processes in European parliamentary and semi-presidential systems Using data from the Comparative Manifesto Project (CMP), the authors propose a new approach that reinterprets error in the coding of CMP data as ambiguity in the actual political positions of parties on the policy dimensions being coded. The range of this error establishes parties' fuzzy preferences. The set of possible outcomes in the process of government formation is then calculated on the basis of both the fuzzy Pareto set and the fuzzy maximal set, and the predictions are compared with those made by two conventional approaches as well as with the government that was actually formed. The comparison shows that, in most cases, the fuzzy approaches outperform their conventional counterparts.
Fuzzy Solution Concepts for Non-cooperative Games: Interval, Fuzzy and Intuitionistic Fuzzy Payoffs (Studies in Fuzziness and Soft Computing #383)
by Amit Kumar Tina VermaThis book proposes novel methods for solving different types of non-cooperative games with interval/fuzzy/intuitionistic fuzzy payoffs. It starts by discussing several existing methods and shows that some mathematically incorrect assumptions have been considered in all these methods. It then proposes solutions to adapt those methods and validate the new proposed methods, such as Gaurika method Ambika-I-IV, Mehar method and others, by using them for solving existing numerical problems. The book offers a comprehensive guide on non-cooperative games with fuzzy payoffs to both students and researchers. It provides them with the all the necessary tools to understand the methods and the theory behind them.
Fuzzy Statistical Inferences Based on Fuzzy Random Variables
by Gholamreza HesamianThis book presents the most commonly used techniques for the most statistical inferences based on fuzzy data. It brings together many of the main ideas used statistical inferences in one place based on fuzzy information including fuzzy data. This book covers a much wider range of topics than a typical introductory text on fuzzy statistics. It includes common topics like elementary probability, descriptive statistics, hypothesis tests, one-way ANOVA, control-charts, reliability systems and regression models The reader is assumed to know calculus and a little fuzzy set theory. The conventional knowledge of probability and statistics is required. Key Features: Includes example in Mathematica and MATLAB. Contains theoretical and applied exercises for each section. Presents various popular methods for analyzing fuzzy data. The book is suitable for students and researchers in statistics, social science, engineering, and economics, and it be used at graduate and P.h.D level.
Fuzzy Stochastic Optimization
by Shuming Wang Junzo WatadaCovering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins by outlining the history and development of the fuzzy random variable before detailing numerous optimization models and applications that include the design of system controls for a dam.
Fuzzy Surfaces in GIS and Geographical Analysis: Theory, Analytical Methods, Algorithms and Applications
by Weldon LodwickSurfaces are a central to geographical analysis. Their generation and manipulation are a key component of geographical information systems (GISs). However, geographical surface data is often not precise. When surfaces are used to model geographical entities, the data inherently contains uncertainty in terms of both position and attribute. Fuzzy