Author: Oscar Castillo
Publisher: Springer Nature
ISBN: 3031597141
Category :
Languages : en
Pages : 102
Book Description
Type-3 Fuzzy Logic in Time Series Prediction
Author: Oscar Castillo
Publisher: Springer Nature
ISBN: 3031597141
Category :
Languages : en
Pages : 102
Book Description
Publisher: Springer Nature
ISBN: 3031597141
Category :
Languages : en
Pages : 102
Book Description
Interval Type-3 Fuzzy Systems: Theory and Design
Author: Oscar Castillo
Publisher: Springer Nature
ISBN: 3030965155
Category : Technology & Engineering
Languages : en
Pages : 109
Book Description
This book briefly reviews the basic concepts of type-2 fuzzy systems and then describes the proposed definitions for interval type-3 fuzzy sets and relations, also interval type-3 inference and systems. The use of type-2 fuzzy systems has become widespread in the leading economy sectors, especially in industrial and application areas, such as services, health, defense, and so on. However, recently the use of interval type-3 fuzzy systems has been receiving increasing attention and some successful applications have been developed in the last year. These issues were taken into consideration for this book, as we did realize that there was a need to offer the main theoretical concepts of type-3 fuzzy logic, as well as methods to design, develop and implement the type-3 fuzzy systems. A review of basic concepts and their use in the design and implementation of interval type-3 fuzzy systems, which are relatively new models of uncertainty and imprecision, are presented. The main focus of this work is based on the basic reasons of the need for interval type-3 fuzzy systems in different areas of application. In addition, we describe methods for designing interval type-3 fuzzy systems and illustrate this with some examples and simulations.
Publisher: Springer Nature
ISBN: 3030965155
Category : Technology & Engineering
Languages : en
Pages : 109
Book Description
This book briefly reviews the basic concepts of type-2 fuzzy systems and then describes the proposed definitions for interval type-3 fuzzy sets and relations, also interval type-3 inference and systems. The use of type-2 fuzzy systems has become widespread in the leading economy sectors, especially in industrial and application areas, such as services, health, defense, and so on. However, recently the use of interval type-3 fuzzy systems has been receiving increasing attention and some successful applications have been developed in the last year. These issues were taken into consideration for this book, as we did realize that there was a need to offer the main theoretical concepts of type-3 fuzzy logic, as well as methods to design, develop and implement the type-3 fuzzy systems. A review of basic concepts and their use in the design and implementation of interval type-3 fuzzy systems, which are relatively new models of uncertainty and imprecision, are presented. The main focus of this work is based on the basic reasons of the need for interval type-3 fuzzy systems in different areas of application. In addition, we describe methods for designing interval type-3 fuzzy systems and illustrate this with some examples and simulations.
Time-Series Prediction and Applications
Author: Amit Konar
Publisher: Springer
ISBN: 3319545973
Category : Technology & Engineering
Languages : en
Pages : 255
Book Description
This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers’ ability and understanding of the topics covered.
Publisher: Springer
ISBN: 3319545973
Category : Technology & Engineering
Languages : en
Pages : 255
Book Description
This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers’ ability and understanding of the topics covered.
New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms
Author: Patricia Melin
Publisher: Springer Nature
ISBN: 3031537130
Category :
Languages : en
Pages : 204
Book Description
Publisher: Springer Nature
ISBN: 3031537130
Category :
Languages : en
Pages : 204
Book Description
Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics
Author: Oscar Castillo
Publisher: Springer Nature
ISBN: 3031289994
Category : Technology & Engineering
Languages : en
Pages : 489
Book Description
In this book, recent theoretical developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are presented in application areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, decision-making, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are a group of papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also a group of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different application areas. In addition, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas. Finally, there are a group of papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.
Publisher: Springer Nature
ISBN: 3031289994
Category : Technology & Engineering
Languages : en
Pages : 489
Book Description
In this book, recent theoretical developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are presented in application areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, decision-making, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are a group of papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also a group of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different application areas. In addition, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas. Finally, there are a group of papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.
Clustering, Classification, and Time Series Prediction by Using Artificial Neural Networks
Author: Patricia Melin
Publisher: Springer Nature
ISBN: 3031711017
Category :
Languages : en
Pages : 82
Book Description
Publisher: Springer Nature
ISBN: 3031711017
Category :
Languages : en
Pages : 82
Book Description
16th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools – ICAFS-2023
Author: Rafik A. Aliev
Publisher: Springer Nature
ISBN: 3031762835
Category :
Languages : en
Pages : 408
Book Description
Publisher: Springer Nature
ISBN: 3031762835
Category :
Languages : en
Pages : 408
Book Description
Fuzzy Modelling
Author: Witold Pedrycz
Publisher: Springer Science & Business Media
ISBN: 1461313651
Category : Mathematics
Languages : en
Pages : 399
Book Description
Fuzzy Modelling: Paradigms and Practice provides an up-to-date and authoritative compendium of fuzzy models, identification algorithms and applications. Chapters in this book have been written by the leading scholars and researchers in their respective subject areas. Several of these chapters include both theoretical material and applications. The editor of this volume has organized and edited the chapters into a coherent and uniform framework. The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models. Fuzzy Modelling: Paradigms and Practice provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.
Publisher: Springer Science & Business Media
ISBN: 1461313651
Category : Mathematics
Languages : en
Pages : 399
Book Description
Fuzzy Modelling: Paradigms and Practice provides an up-to-date and authoritative compendium of fuzzy models, identification algorithms and applications. Chapters in this book have been written by the leading scholars and researchers in their respective subject areas. Several of these chapters include both theoretical material and applications. The editor of this volume has organized and edited the chapters into a coherent and uniform framework. The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models. Fuzzy Modelling: Paradigms and Practice provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.
Analysis and Design of Intelligent Systems Using Soft Computing Techniques
Author: Patricia Melin
Publisher: Springer Science & Business Media
ISBN: 3540724311
Category : Computers
Languages : en
Pages : 856
Book Description
This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.
Publisher: Springer Science & Business Media
ISBN: 3540724311
Category : Computers
Languages : en
Pages : 856
Book Description
This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.
Soft Computing and Optimization
Author: Syeda Darakhshan Jabeen
Publisher: Springer Nature
ISBN: 9811964068
Category : Mathematics
Languages : en
Pages : 362
Book Description
This book collects papers presented at the Virtual International Conference on Soft Computing, Optimization Theory and Applications (SCOTA 2021), held at the Birla Institute of Technology, Mesra, Ranchi, India, from 26–27 March 2021. Topics discussed in the book are on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book highlights research on: (a) hybrid intelligent systems based on soft computing, new concepts and algorithms based on fuzzy logic and their applications, (b) theory and practice of meta-heuristics in different areas of application, (c) applications of fuzzy logic, (d) neural networks and hybrid intelligent systems in medical applications, (e) neural networks and optimization and evolutionary algorithms and their different applications and (f) applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems. Some papers contain applications background like approximate solution of fractional differential equations via fixed-point algorithms and applications to equilibrium problems and image deburring problems. The book will be of great use to students, researchers and scientists in computer science, optimization and engineering, and those interested on computational intelligence and soft computing and their applications.
Publisher: Springer Nature
ISBN: 9811964068
Category : Mathematics
Languages : en
Pages : 362
Book Description
This book collects papers presented at the Virtual International Conference on Soft Computing, Optimization Theory and Applications (SCOTA 2021), held at the Birla Institute of Technology, Mesra, Ranchi, India, from 26–27 March 2021. Topics discussed in the book are on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book highlights research on: (a) hybrid intelligent systems based on soft computing, new concepts and algorithms based on fuzzy logic and their applications, (b) theory and practice of meta-heuristics in different areas of application, (c) applications of fuzzy logic, (d) neural networks and hybrid intelligent systems in medical applications, (e) neural networks and optimization and evolutionary algorithms and their different applications and (f) applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems. Some papers contain applications background like approximate solution of fractional differential equations via fixed-point algorithms and applications to equilibrium problems and image deburring problems. The book will be of great use to students, researchers and scientists in computer science, optimization and engineering, and those interested on computational intelligence and soft computing and their applications.