Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control

Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control

Author: Oscar Castillo

Publisher: Springer

Published: 2009-10-13

Total Pages: 320

ISBN-13: 3642045146

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We describe in this book, new methods for evolutionary design of intelligent s- tems using soft computing and their applications in modeling, simulation and c- trol. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in four main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of evolutionary design of fuzzy systems in intelligent control, which consists of papers that propose new methods for designing and optimizing intelligent controllers for different applications. The second part c- tains papers with the main theme of evolutionary design of intelligent systems for pattern recognition applications, which are basically papers using evolutionary al- rithms for optimizing modular neural networks with fuzzy systems for response - tegration, for achieving pattern recognition in different applications. The third part contains papers with the themes of models for learning and social simulation, which are papers that apply intelligent systems to the problems of designing learning - jects and social agents. The fourth part contains papers that deal with intelligent s- tems in robotics applications and hardware implementations. In the part of Intelligent Control there are 5 papers that describe different c- tributions on evolutionary optimization of fuzzy systems in intelligent control. The first paper, by Ricardo Martinez-Marroquin et al.


Book Synopsis Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control by : Oscar Castillo

Download or read book Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control written by Oscar Castillo and published by Springer. This book was released on 2009-10-13 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: We describe in this book, new methods for evolutionary design of intelligent s- tems using soft computing and their applications in modeling, simulation and c- trol. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in four main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of evolutionary design of fuzzy systems in intelligent control, which consists of papers that propose new methods for designing and optimizing intelligent controllers for different applications. The second part c- tains papers with the main theme of evolutionary design of intelligent systems for pattern recognition applications, which are basically papers using evolutionary al- rithms for optimizing modular neural networks with fuzzy systems for response - tegration, for achieving pattern recognition in different applications. The third part contains papers with the themes of models for learning and social simulation, which are papers that apply intelligent systems to the problems of designing learning - jects and social agents. The fourth part contains papers that deal with intelligent s- tems in robotics applications and hardware implementations. In the part of Intelligent Control there are 5 papers that describe different c- tributions on evolutionary optimization of fuzzy systems in intelligent control. The first paper, by Ricardo Martinez-Marroquin et al.

Nature-Inspired Design of Hybrid Intelligent Systems

Nature-Inspired Design of Hybrid Intelligent Systems

Author: Patricia Melin

Publisher: Springer

Published: 2016-12-08

Total Pages: 817

ISBN-13: 331947054X

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This book highlights recent advances in the design of hybrid intelligent systems based on 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 divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.


Book Synopsis Nature-Inspired Design of Hybrid Intelligent Systems by : Patricia Melin

Download or read book Nature-Inspired Design of Hybrid Intelligent Systems written by Patricia Melin and published by Springer. This book was released on 2016-12-08 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent advances in the design of hybrid intelligent systems based on 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 divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

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: Patricia Melin

Publisher: Springer

Published: 2015-06-12

Total Pages: 612

ISBN-13: 3319177478

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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.


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

Download or read book Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization written by Patricia Melin and published by Springer. This book was released on 2015-06-12 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Recent Advances on Hybrid Intelligent Systems

Recent Advances on Hybrid Intelligent Systems

Author: Oscar Castillo

Publisher: Springer

Published: 2012-09-14

Total Pages: 558

ISBN-13: 3642330215

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This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for achieving efficient pattern recognition or time series prediction. The third part contains papers with the theme of bio-inspired and genetic optimization methods, which basically consider the proposal of new methods and applications of bio-inspired optimization to solve complex optimization of real problems. The fourth part contains papers that deal with the application of intelligent optimization techniques in real world problems in scheduling, planning and manufacturing. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.


Book Synopsis Recent Advances on Hybrid Intelligent Systems by : Oscar Castillo

Download or read book Recent Advances on Hybrid Intelligent Systems written by Oscar Castillo and published by Springer. This book was released on 2012-09-14 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for achieving efficient pattern recognition or time series prediction. The third part contains papers with the theme of bio-inspired and genetic optimization methods, which basically consider the proposal of new methods and applications of bio-inspired optimization to solve complex optimization of real problems. The fourth part contains papers that deal with the application of intelligent optimization techniques in real world problems in scheduling, planning and manufacturing. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.

Type-2 Fuzzy Logic in Intelligent Control Applications

Type-2 Fuzzy Logic in Intelligent Control Applications

Author: Oscar Castillo

Publisher: Springer Science & Business Media

Published: 2011-10-18

Total Pages: 187

ISBN-13: 3642246621

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We describe in this book, hybrid intelligent systems based mainly on type-2 fuzzy logic for intelligent control. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. The book is organized in three main parts, which contain a group of chapters around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which can be the basis for achieving intelligent control with interval type-2 fuzzy logic. The second part of the book is comprised of chapters with the main theme of evolutionary optimization of type-2 fuzzy systems in intelligent control with the aim of designing optimal type-2 fuzzy controllers for complex control problems in diverse areas of application, including mobile robotics, aircraft dynamics systems and hardware implementations. The third part of the book is formed with chapters dealing with the theme of bio-inspired optimization of type-2 fuzzy systems in intelligent control, which includes the application of particle swarm intelligence and ant colony optimization algorithms for obtaining optimal type-2 fuzzy controllers.


Book Synopsis Type-2 Fuzzy Logic in Intelligent Control Applications by : Oscar Castillo

Download or read book Type-2 Fuzzy Logic in Intelligent Control Applications written by Oscar Castillo and published by Springer Science & Business Media. This book was released on 2011-10-18 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: We describe in this book, hybrid intelligent systems based mainly on type-2 fuzzy logic for intelligent control. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. The book is organized in three main parts, which contain a group of chapters around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which can be the basis for achieving intelligent control with interval type-2 fuzzy logic. The second part of the book is comprised of chapters with the main theme of evolutionary optimization of type-2 fuzzy systems in intelligent control with the aim of designing optimal type-2 fuzzy controllers for complex control problems in diverse areas of application, including mobile robotics, aircraft dynamics systems and hardware implementations. The third part of the book is formed with chapters dealing with the theme of bio-inspired optimization of type-2 fuzzy systems in intelligent control, which includes the application of particle swarm intelligence and ant colony optimization algorithms for obtaining optimal type-2 fuzzy controllers.

Recent Advances on Hybrid Approaches for Designing Intelligent Systems

Recent Advances on Hybrid Approaches for Designing Intelligent Systems

Author: Oscar Castillo

Publisher: Springer

Published: 2014-03-26

Total Pages: 702

ISBN-13: 3319051709

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This book describes recent advances on hybrid intelligent systems using soft computing techniques for diverse areas of application, such as intelligent control and robotics, pattern recognition, time series prediction and optimization complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of type-2 fuzzy logic, which basically consists of papers that propose new models and applications for type-2 fuzzy systems. The second part contains papers with the main theme of bio-inspired optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application. The third part contains papers that deal with new models and applications of neural networks in real world problems. The fourth part contains papers with the theme of intelligent optimization methods, which basically consider the proposal of new methods of optimization to solve complex real world optimization problems. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.


Book Synopsis Recent Advances on Hybrid Approaches for Designing Intelligent Systems by : Oscar Castillo

Download or read book Recent Advances on Hybrid Approaches for Designing Intelligent Systems written by Oscar Castillo and published by Springer. This book was released on 2014-03-26 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes recent advances on hybrid intelligent systems using soft computing techniques for diverse areas of application, such as intelligent control and robotics, pattern recognition, time series prediction and optimization complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of type-2 fuzzy logic, which basically consists of papers that propose new models and applications for type-2 fuzzy systems. The second part contains papers with the main theme of bio-inspired optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application. The third part contains papers that deal with new models and applications of neural networks in real world problems. The fourth part contains papers with the theme of intelligent optimization methods, which basically consider the proposal of new methods of optimization to solve complex real world optimization problems. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.

Evolutionary Algorithms and Chaotic Systems

Evolutionary Algorithms and Chaotic Systems

Author: Ivan Zelinka

Publisher: Springer Science & Business Media

Published: 2010-02-23

Total Pages: 533

ISBN-13: 3642107060

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This book discusses the mutual intersection of two fields of research: evolutionary computation, which can handle tasks such as control of various chaotic systems, and deterministic chaos, which is investigated as a behavioral part of evolutionary algorithms.


Book Synopsis Evolutionary Algorithms and Chaotic Systems by : Ivan Zelinka

Download or read book Evolutionary Algorithms and Chaotic Systems written by Ivan Zelinka and published by Springer Science & Business Media. This book was released on 2010-02-23 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the mutual intersection of two fields of research: evolutionary computation, which can handle tasks such as control of various chaotic systems, and deterministic chaos, which is investigated as a behavioral part of evolutionary algorithms.

Multi-Objective Swarm Intelligent Systems

Multi-Objective Swarm Intelligent Systems

Author: Leandro dos Santos Coelho

Publisher: Springer

Published: 2009-11-23

Total Pages: 228

ISBN-13: 3642051650

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This book covers the latest in multi-objective swarm intelligence and cooperative behavior. It contains innovative and intriguing applications as well as additions to the methodology and theory of genetic programming.


Book Synopsis Multi-Objective Swarm Intelligent Systems by : Leandro dos Santos Coelho

Download or read book Multi-Objective Swarm Intelligent Systems written by Leandro dos Santos Coelho and published by Springer. This book was released on 2009-11-23 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest in multi-objective swarm intelligence and cooperative behavior. It contains innovative and intriguing applications as well as additions to the methodology and theory of genetic programming.

Uncertainty Approaches for Spatial Data Modeling and Processing

Uncertainty Approaches for Spatial Data Modeling and Processing

Author: Frederick E. Petry

Publisher: Springer

Published: 2010-03-10

Total Pages: 202

ISBN-13: 3642106633

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We are facing an immense growth of digital data and information resources, both in terms of size, complexity, modalities and intrusiveness. Almost every aspect of our existence is being digitally captured. This is exemplified by the omnipresent existence of all kinds of data storage, far beyond those stored in traditional relational databases. The spectrum of data being digitally stored runs from multimedia data repositories to your purchases in most stores. Every tweet that you broadcast is captured for posterity. Needless to say this situation posses new research opportunities, challenges and problems in the ways we store, manipulate, search, and - in general - make use of such data and information. Attempts to cope with these problems have been emerging all over the world with thousands of people devoted to developing tools and techniques to deal with this new area of research. One of the prominent scholars and researchers in this field was the late Professor Ashley Morris who died suddenly and tragically at a young age. Ashley's career begun in industry, where he specialized in databases.


Book Synopsis Uncertainty Approaches for Spatial Data Modeling and Processing by : Frederick E. Petry

Download or read book Uncertainty Approaches for Spatial Data Modeling and Processing written by Frederick E. Petry and published by Springer. This book was released on 2010-03-10 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are facing an immense growth of digital data and information resources, both in terms of size, complexity, modalities and intrusiveness. Almost every aspect of our existence is being digitally captured. This is exemplified by the omnipresent existence of all kinds of data storage, far beyond those stored in traditional relational databases. The spectrum of data being digitally stored runs from multimedia data repositories to your purchases in most stores. Every tweet that you broadcast is captured for posterity. Needless to say this situation posses new research opportunities, challenges and problems in the ways we store, manipulate, search, and - in general - make use of such data and information. Attempts to cope with these problems have been emerging all over the world with thousands of people devoted to developing tools and techniques to deal with this new area of research. One of the prominent scholars and researchers in this field was the late Professor Ashley Morris who died suddenly and tragically at a young age. Ashley's career begun in industry, where he specialized in databases.

Computational Intelligence in Intelligent Data Analysis

Computational Intelligence in Intelligent Data Analysis

Author: Christian Moewes

Publisher: Springer

Published: 2012-08-23

Total Pages: 298

ISBN-13: 3642323782

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Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.


Book Synopsis Computational Intelligence in Intelligent Data Analysis by : Christian Moewes

Download or read book Computational Intelligence in Intelligent Data Analysis written by Christian Moewes and published by Springer. This book was released on 2012-08-23 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.