Ebook: Soft Computing Applications in Optimization, Control, and Recognition
- Tags: Computational Intelligence, Artificial Intelligence (incl. Robotics), Pattern Recognition
- Series: Studies in Fuzziness and Soft Computing 294
- Year: 2013
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.
Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.
Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.
Content:
Front Matter....Pages 1-7
Front Matter....Pages 1-1
Optimization of Type-2 and Type-1 Fuzzy Tracking Controllers for an Autonomous Mobile Robot under Perturbed Torques by Means of a Chemical Optimization Paradigm....Pages 3-26
A Genetic Algorithm for the Problem of Minimal Brauer Chains for Large Exponents....Pages 27-51
Cellular Processing Algorithms....Pages 53-74
Front Matter....Pages 75-75
Hierarchical Genetic Optimization of the Fuzzy Integrator for Navigation of a Mobile Robot....Pages 77-96
Particle Swarm Optimization for Multi-objective Control Design Using AT2-FLC in FPGA Device....Pages 97-124
Genetic Optimization of Modular Type-1 Fuzzy Controllers for Complex Control Problems....Pages 125-154
Front Matter....Pages 155-155
Multi-Objective Hierarchical Genetic Algorithm for Modular Granular Neural Network Optimization....Pages 157-185
Type-2 Fuzzy Weight Adjustment for Backpropagation in Prediction Time Series and Pattern Recognition....Pages 187-213
Brain Computer Interface Development Based on Recurrent Neural Networks and ANFIS Systems....Pages 215-236
Front Matter....Pages 237-237
An Analysis of the Relationship between the Size of the Clusters and the Principle of Justifiable Granularity in Clustering Algorithms....Pages 239-263
Type-2 Fuzzy Logic Grammars in Language Evolution....Pages 265-286
Methodology of Design: A Novel Generic Approach Applied to the Course Timetabling Problem....Pages 287-319
High-Performance Architecture for the Modified NSGA-II....Pages 321-341
Back Matter....Pages 0--1
Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.
Content:
Front Matter....Pages 1-7
Front Matter....Pages 1-1
Optimization of Type-2 and Type-1 Fuzzy Tracking Controllers for an Autonomous Mobile Robot under Perturbed Torques by Means of a Chemical Optimization Paradigm....Pages 3-26
A Genetic Algorithm for the Problem of Minimal Brauer Chains for Large Exponents....Pages 27-51
Cellular Processing Algorithms....Pages 53-74
Front Matter....Pages 75-75
Hierarchical Genetic Optimization of the Fuzzy Integrator for Navigation of a Mobile Robot....Pages 77-96
Particle Swarm Optimization for Multi-objective Control Design Using AT2-FLC in FPGA Device....Pages 97-124
Genetic Optimization of Modular Type-1 Fuzzy Controllers for Complex Control Problems....Pages 125-154
Front Matter....Pages 155-155
Multi-Objective Hierarchical Genetic Algorithm for Modular Granular Neural Network Optimization....Pages 157-185
Type-2 Fuzzy Weight Adjustment for Backpropagation in Prediction Time Series and Pattern Recognition....Pages 187-213
Brain Computer Interface Development Based on Recurrent Neural Networks and ANFIS Systems....Pages 215-236
Front Matter....Pages 237-237
An Analysis of the Relationship between the Size of the Clusters and the Principle of Justifiable Granularity in Clustering Algorithms....Pages 239-263
Type-2 Fuzzy Logic Grammars in Language Evolution....Pages 265-286
Methodology of Design: A Novel Generic Approach Applied to the Course Timetabling Problem....Pages 287-319
High-Performance Architecture for the Modified NSGA-II....Pages 321-341
Back Matter....Pages 0--1
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