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Fuzzy Cognitive Maps for Applied Sciences and Engineering
by Elpiniki I. PapageorgiouFuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to "concepts" bearing different states of activation depending on the knowledge they represent, and the "edges" denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful modeling results. The aim of this book is to fill the existing gap in the literature concerning fundamentals, models, extensions and learning algorithms for FCMs in knowledge engineering. It comprehensively covers the state-of-the-art FCM modeling and learning methods, with algorithms, codes and software tools, and provides a set of applications that demonstrate their various usages in applied sciences and engineering.
Fuzzy Cognitive Maps: Best Practices and Modern Methods
by Philippe J. Giabbanelli Gonzalo NápolesThis book starts with the rationale for creating an FCM by contrast to other techniques for participatory modeling, as this rationale is a key element to justify the adoption of techniques in a research paper. Fuzzy cognitive mapping is an active research field with over 20,000 publications devoted to externalizing the qualitative perspectives or “mental models” of individuals and groups. Since the emergence of fuzzy cognitive maps (FCMs) back in the 80s, new algorithms have been developed to reduce bias, facilitate the externalization process, or efficiently utilize quantitative data via machine learning. It covers the development of an FCM with participants through a traditional in-person setting, drawing from the experience of practitioners and highlighting solutions to commonly encountered challenges. The book continues with introducing principles of simulations with FCMs as a tool to perform what-if scenario analysis, while extending those principles to more elaborated simulation scenarios where FCMs and agent-based modeling are combined. Once an FCM model is obtained, the book then details the analytical tools available for practitioners (e.g., to identify the most important factors) and provides examples to aid in the interpretation of results. The discussion concerning relevant extensions is equally pertinent, which are devoted to increasing the expressiveness of the FCM formalism in problems involving uncertainty. The last four chapters focus on building FCM models from historical data. These models are typically needed when facing multi-output prediction or pattern classification problems. In that regard, the book smoothly guides the reader from simple approaches to more elaborated algorithms, symbolizing the noticeable progress of this field in the last 35 years. Problems, recent references, and functional codes are included in each chapter to provide practice and support further learning from practitioners and researchers.
Fuzzy Decision-Making Methods Based on Prospect Theory and Its Application in Venture Capital (Uncertainty and Operations Research)
by Zeshui Xu Xiaoli TianThis book gives a thorough and systematic introduction to the latest research results about fuzzy decision-making method based on prospect theory. It includes eight chapters: Introduction, Intuitionistic fuzzy MADM based on prospect theory, QUALIFLEX based on prospect theory with probabilistic linguistic information, Group PROMETHEE based on prospect theory with hesitant fuzzy linguistic information, Prospect consensus with probabilistic hesitant fuzzy preference information, Improved TODIM based on prospect theory and the improved TODIM with probabilistic hesitant fuzzy information, etc. This book is suitable for the researchers in the fields of fuzzy mathematics, operations research, behavioral science, management science and engineering, etc. It is also useful as a textbook for postgraduate and senior-year undergraduate students of the relevant professional institutions of higher learning.
Fuzzy Differential Equations and Applications for Engineers and Scientists
by Smita Tapaswini Diptiranjan Behera S. ChakravertyDifferential equations play a vital role in the modeling of physical and engineering problems, such as those in solid and fluid mechanics, viscoelasticity, biology, physics, and many other areas. In general, the parameters, variables and initial conditions within a model are considered as being defined exactly. In reality there may be only vague, imprecise or incomplete information about the variables and parameters available. This can result from errors in measurement, observation, or experimental data; application of different operating conditions; or maintenance induced errors. To overcome uncertainties or lack of precision, one can use a fuzzy environment in parameters, variables and initial conditions in place of exact (fixed) ones, by turning general differential equations into Fuzzy Differential Equations ("FDEs"). In real applications it can be complicated to obtain exact solution of fuzzy differential equations due to complexities in fuzzy arithmetic, creating the need for use of reliable and efficient numerical techniques in the solution of fuzzy differential equations. These include fuzzy ordinary and partial, fuzzy linear and nonlinear, and fuzzy arbitrary order differential equations. This unique work?provides a new direction for the reader in the use of basic concepts of fuzzy differential equations, solutions and its applications. It can serve as an essential reference work for students, scholars, practitioners, researchers and academicians in engineering and science who need to model uncertain physical problems.
Fuzzy Differential Equations in Various Approaches
by Luciana Takata Gomes Laécio Carvalho de Barros Barnabas BedeThis book may be used as reference for graduate students interested in fuzzy differential equations and researchers working in fuzzy sets and systems, dynamical systems, uncertainty analysis, and applications of uncertain dynamical systems. Beginning with a historical overview and introduction to fundamental notions of fuzzy sets, including different possibilities of fuzzy differentiation and metric spaces, this book moves on to an overview of fuzzy calculus thorough exposition and comparison of different approaches. Innovative theories of fuzzy calculus and fuzzy differential equations using fuzzy bunches of functions are introduced and explored. Launching with a brief review of essential theories, this book investigates both well-known and novel approaches in this field; such as the Hukuhara differentiability and its generalizations as well as differential inclusions and Zadeh's extension. Through a unique analysis, results of all these theories are examined and compared.
Fuzzy Dynamic Equations, Dynamic Inclusions, and Optimal Control Problems on Time Scales
by Svetlin G. GeorgievThe theory of dynamic equations has many interesting applications in control theory, mathematical economics, mathematical biology, engineering and technology. In some cases, there exists uncertainty, ambiguity, or vague factors in such problems, and fuzzy theory and interval analysis are powerful tools for modeling these equations on time scales. The aim of this book is to present a systematic account of recent developments; describe the current state of the useful theory; show the essential unity achieved in the theory fuzzy dynamic equations, dynamic inclusions and optimal control problems on time scales; and initiate several new extensions to other types of fuzzy dynamic systems and dynamic inclusions. The material is presented in a highly readable, mathematically solid format. Many practical problems are illustrated, displaying a wide variety of solution techniques. The book is primarily intended for senior undergraduate students and beginning graduate students of engineering and science courses. Students in mathematical and physical sciences will find many sections of direct relevance.
Fuzzy Geometric Programming Techniques and Applications (Forum for Interdisciplinary Mathematics)
by Sahidul Islam Wasim Akram MandalThis book develops the concepts of various unique optimization techniques in the crisp and fuzzy environment. It provides an extensive overview of geometric programming methods within a unifying framework, and presents an in-depth discussion of the modified geometric programming problem, fuzzy geometric programming, as well as new insights into goal geometric programming. With numerous examples and exercises together with detailed solutions for several problems, the book also addresses fuzzy multi-objective geometric programming techniques. Geometric programming, which falls into the general class of signomial problems, has applications across disciplines, from engineering to economics, and is extremely useful in applications of a variety of optimization problems. Organized into thirteen chapters, this book is a valuable resource for graduate and advanced undergraduate students and researchers in applied mathematics and engineering.
Fuzzy Graph Theory with Applications to Human Trafficking (Studies in Fuzziness and Soft Computing #365)
by John N. Mordeson Sunil Mathew Davender S. MalikThis book reports on advanced concepts in fuzzy graph theory, showing a set of tools that can be successfully applied to understanding and modeling illegal human trafficking. Building on the previous book on fuzzy graph by the same authors, which set the fundamentals for readers to understand this developing field of research, this second book gives a special emphasis to applications of the theory. For this, authors introduce new concepts, such as intuitionistic fuzzy graphs, the concept of independence and domination in fuzzy graphs, as well as directed fuzzy networks, incidence graphs and many more.
Fuzzy Hypergraphs and Related Extensions (Studies in Fuzziness and Soft Computing #390)
by Muhammad Akram Anam LuqmanThis book presents the fundamental and technical concepts of fuzzy hypergraphs and explains their extensions and applications. It discusses applied generalized mathematical models of hypergraphs, including complex, intuitionistic, bipolar, m-polar fuzzy, Pythagorean, complex Pythagorean, and q-rung orthopair hypergraphs, as well as single-valued neutrosophic, complex neutrosophic and bipolar neutrosophic hypergraphs. In addition, the book also sheds light on real-world applications of these hypergraphs, making it a valuable resource for students and researchers in the field of mathematics, as well as computer and social scientists.
Fuzzy Information and Engineering-2019 (Advances in Intelligent Systems and Computing #1094)
by Bing-Yuan CaoThis book includes 70 selected papers from the Ninth International Conference on Fuzzy Information and Engineering (ICFIE) Satellite, which was held on December 26–30, 2018; and from the 9th International Conference on Fuzzy Information and Engineering (ICFIAE), which was held on February 13–15, 2019. The two conferences presented the latest research in the areas of fuzzy information and engineering, operational research and management, and their applications.
Fuzzy Lie Algebras (Infosys Science Foundation Series)
by Muhammad AkramThis book explores certain structures of fuzzy Lie algebras, fuzzy Lie superalgebras and fuzzy n-Lie algebras. In addition, it applies various concepts to Lie algebras and Lie superalgebras, including type-1 fuzzy sets, interval-valued fuzzy sets, intuitionistic fuzzy sets, interval-valued intuitionistic fuzzy sets, vague sets and bipolar fuzzy sets. The book offers a valuable resource for students and researchers in mathematics, especially those interested in fuzzy Lie algebraic structures, as well as for other scientists. Divided into 10 chapters, the book begins with a concise review of fuzzy set theory, Lie algebras and Lie superalgebras. In turn, Chap. 2 discusses several properties of concepts like interval-valued fuzzy Lie ideals, characterizations of Noetherian Lie algebras, quotient Lie algebras via interval-valued fuzzy Lie ideals, and interval-valued fuzzy Lie superalgebras. Chaps. 3 and 4 focus on various concepts of fuzzy Lie algebras, while Chap. 5 presents the concept of fuzzy Lie ideals of a Lie algebra over a fuzzy field. Chapter 6 is devoted to the properties of bipolar fuzzy Lie ideals, bipolar fuzzy Lie subsuperalgebras, bipolar fuzzy bracket product, solvable bipolar fuzzy Lie ideals and nilpotent bipolar fuzzy Lie ideals. Chap. 7 deals with the properties of m-polar fuzzy Lie subalgebras and m-polar fuzzy Lie ideals, while Chap. 8 addresses concepts like soft intersection Lie algebras and fuzzy soft Lie algebras. Chap. 9 deals with rough fuzzy Lie subalgebras and rough fuzzy Lie ideals, and lastly, Chap. 10 investigates certain properties of fuzzy subalgebras and ideals of n-ary Lie algebras.
Fuzzy Logic
by Enric Trillas Luka EciolazaThis book introduces readers to fundamental concepts in fuzzy logic. It describes the necessary theoretical background and a number of basic mathematical models. Moreover, it makes them familiar with fuzzy control, an important topic in the engineering field. The book offers an unconventional introductory textbook on fuzzy logic, presenting theory together with examples and not always following the typical mathematical style of theorem-corollaries. Primarily intended to support engineers during their university studies, and to spark their curiosity about fuzzy logic and its applications, the book is also suitable for self-study, providing a valuable resource for engineers and professionals who deal with imprecision and non-random uncertainty in real-world applications.
Fuzzy Logic Applications in Computer Science and Mathematics
by Dac-Nhuong Le Gunjan Mukherjee Ashok Kumar Shaw Biswadip Basu Mallik Rahul KarFUZZY LOGIC APPLICATIONS IN COMPUTER SCIENCE AND MATHEMATICSTICS The prime objective of developing this book is to provide meticulous details about the basic and advanced concepts of fuzzy logic and its all-around applications to different fields of mathematics and engineering. The basic steps of fuzzy inference systems starting from the core foundation of the fuzzy concepts are presented in this book. The fuzzy theory is a mathematical concept and, at the same time, it is applied to many versatile engineering fields and research domains related to computer science. The fuzzy system offers some knowledge about uncertainty and is also related to the theory of probability. A fuzzy logic-based model acts as the classifier for many different types of data belonging to several classes. Covered in this book are topics such as the fundamental concepts of mathematics, fuzzy logic concepts, probability and possibility theories, and evolutionary computing to some extent. The combined fields of neural network and fuzzy domain (known as the neuro-fuzzy system) are explained and elaborated. Each chapter has been produced in a very lucid manner, with grading from simple to complex to accommodate the anticipated different audiences. The application-oriented approach is the unique feature of this book. Audience This book will be read and used by a broad audience including applied mathematicians, computer scientists, and industry engineers.
Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics
by Oscar Castillo Patricia MelinThis book describes recent advances on fuzzy logic augmentation of nature-inspired optimization metaheuristics and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in two main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic augmentation of nature-inspired optimization metaheuristics, which basically consists of papers that propose new optimization algorithms enhanced using fuzzy systems. The second part contains papers with the main theme of application of optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application.
Fuzzy Logic Based Power-Efficient Real-Time Multi-Core System
by Jameel Ahmed Mohammed Yakoob Siyal Shaheryar Najam Zohaib NajamThis book focuses on identifying the performance challenges involved in computer architectures, optimal configuration settings and analysing their impact on the performance of multi-core architectures. Proposing a power and throughput-aware fuzzy-logic-based reconfiguration for Multi-Processor Systems on Chip (MPSoCs) in both simulation and real-time environments, it is divided into two major parts. The first part deals with the simulation-based power and throughput-aware fuzzy logic reconfiguration for multi-core architectures, presenting the results of a detailed analysis on the factors impacting the power consumption and performance of MPSoCs. In turn, the second part highlights the real-time implementation of fuzzy-logic-based power-efficient reconfigurable multi-core architectures for Intel and Leone3 processors.
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.