Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics

Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics
Author :
Publisher : Springer Nature
Total Pages : 489
Release :
ISBN-10 : 9783031289996
ISBN-13 : 3031289994
Rating : 4/5 (96 Downloads)

Synopsis Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics by : Oscar Castillo

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.

New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics

New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics
Author :
Publisher : Springer Nature
Total Pages : 471
Release :
ISBN-10 : 9783031082665
ISBN-13 : 3031082664
Rating : 4/5 (65 Downloads)

Synopsis New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics by : Oscar Castillo

In this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are applied to areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, 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 some 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 some papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers describe 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 areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications
Author :
Publisher : Springer Nature
Total Pages : 383
Release :
ISBN-10 : 9783030687762
ISBN-13 : 3030687767
Rating : 4/5 (62 Downloads)

Synopsis Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications by : Oscar Castillo

We describe in this book, recent developments 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 contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some 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 some papers that presents theory and practice of meta-heuristics in different areas of application. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.

Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design

Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design
Author :
Publisher : Springer Nature
Total Pages : 254
Release :
ISBN-10 : 9783031220425
ISBN-13 : 3031220420
Rating : 4/5 (25 Downloads)

Synopsis Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design by : Oscar Castillo

This book covers recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations. In addition, the above-mentioned methods are applied to areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Nowadays, the main topic of the book is highly relevant, as most current intelligent systems and devices in use utilize some form of intelligent feature to enhance their performance. In addition, on the theoretical side, new and advanced models and algorithms of type-2 and type-3 fuzzy logic are presented, which are of great interest to researchers working on these areas. Also, new nature-inspired optimization algorithms and innovative neural models are put forward in the manuscript, which are very popular subjects, at this moment. There are contributions on theoretical aspects as well as applications, which make the book very appealing to a wide audience, ranging from researchers to professors and graduate students.

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications

Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications
Author :
Publisher :
Total Pages : 0
Release :
ISBN-10 : 3030687775
ISBN-13 : 9783030687779
Rating : 4/5 (75 Downloads)

Synopsis Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications by : Oscar Castillo

We describe in this book, recent developments 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 contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some 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 some papers that presents theory and practice of meta-heuristics in different areas of application. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems. .

Intelligent and Fuzzy Systems

Intelligent and Fuzzy Systems
Author :
Publisher : Springer Nature
Total Pages : 833
Release :
ISBN-10 : 9783031397745
ISBN-13 : 3031397746
Rating : 4/5 (45 Downloads)

Synopsis Intelligent and Fuzzy Systems by : Cengiz Kahraman

This book consists of the papers accepted after a careful review process at an international scientific meeting where the latest developments on intelligent and fuzzy systems are presented and discussed. The latest developments in both the theoretical and practical fields of the new fuzzy set extensions have been prepared by expert researchers. Contributed by participants from more than 40 different countries, this book is also a useful resource in terms of showing the levels that fuzzy and intelligent systems have reached in various countries of the world. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc., and Ph.D. students studying fuzzy sets and artificial intelligence. The book covers fuzzy logic theory and applications, heuristics, and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.

Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization
Author :
Publisher : Springer
Total Pages : 612
Release :
ISBN-10 : 9783319177472
ISBN-13 : 3319177478
Rating : 4/5 (72 Downloads)

Synopsis Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization by : Patricia Melin

This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization 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 eight 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, which basically consists of papers that propose new concepts and algorithms based on fuzzy systems. The second part contains papers with the main theme of neural networks theory, which are basically papers dealing with new concepts and algorithms in neural networks. The third part contains papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The fourth part contains papers describing new nature-inspired optimization algorithms. The fifth part presents diverse applications of nature-inspired optimization algorithms. The sixth part contains papers describing new optimization algorithms. The seventh part contains papers describing applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. Finally, the eighth part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques.