Ebook: Computational Intelligence: Engineering of Hybrid Systems
- Tags: Appl.Mathematics/Computational Methods of Engineering, Artificial Intelligence (incl. Robotics), Applications of Mathematics, Bioinformatics, Operations Research/Decision Theory
- Series: Studies in Fuzziness and Soft Computing 174
- Year: 2005
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
Hybrid Intelligent Systems has become an important research topic in computer science and application field in science and engineering. This book offers a gentle introduction to the engineering aspects of hybrid intelligent systems, also emphasizing the interrelation with the main intelligent technologies such as genetic algorithms – evolutionary computation, neural networks, fuzzy systems, evolvable hardware, DNA computing, artificial immune systems. A unitary whole of theory and application, the book provides readers with the fundamentals, background information, and practical methods for building a hybrid intelligent system. It treats a panoply of applications including many in industry, educational systems, forecasting, financial engineering, and bioinformatics. This volume is useful to newcomers in the field because it quickly familiarizes them with engineering elements of developing hybrid intelligent systems and a wide range of real applications, including non-industrial applications. Researchers, developers and technically oriented managers can use the book for developing both new hybrid intelligent systems approaches and new applications requiring the hybridization of the typical tools and concepts to Computational Intelligence.
Hybrid Intelligent Systems has become an important research topic in computer science and application field in science and engineering. This book offers a gentle introduction to the engineering aspects of hybrid intelligent systems, also emphasizing the interrelation with the main intelligent technologies such as genetic algorithms – evolutionary computation, neural networks, fuzzy systems, evolvable hardware, DNA computing, artificial immune systems. A unitary whole of theory and application, the book provides readers with the fundamentals, background information, and practical methods for building a hybrid intelligent system. It treats a panoply of applications including many in industry, educational systems, forecasting, financial engineering, and bioinformatics. This volume is useful to newcomers in the field because it quickly familiarizes them with engineering elements of developing hybrid intelligent systems and a wide range of real applications, including non-industrial applications. Researchers, developers and technically oriented managers can use the book for developing both new hybrid intelligent systems approaches and new applications requiring the hybridization of the typical tools and concepts to Computational Intelligence.
Hybrid Intelligent Systems has become an important research topic in computer science and application field in science and engineering. This book offers a gentle introduction to the engineering aspects of hybrid intelligent systems, also emphasizing the interrelation with the main intelligent technologies such as genetic algorithms – evolutionary computation, neural networks, fuzzy systems, evolvable hardware, DNA computing, artificial immune systems. A unitary whole of theory and application, the book provides readers with the fundamentals, background information, and practical methods for building a hybrid intelligent system. It treats a panoply of applications including many in industry, educational systems, forecasting, financial engineering, and bioinformatics. This volume is useful to newcomers in the field because it quickly familiarizes them with engineering elements of developing hybrid intelligent systems and a wide range of real applications, including non-industrial applications. Researchers, developers and technically oriented managers can use the book for developing both new hybrid intelligent systems approaches and new applications requiring the hybridization of the typical tools and concepts to Computational Intelligence.
Content:
Front Matter....Pages -
Intelligent Techniques and Computational Intelligence....Pages 1-11
Neuro-Fuzzy Based Hybrid Intelligent Systems for Fault Diagnosis....Pages 13-24
Neuro-Fuzzy Integration in Hybrid Intelligent Systems....Pages 25-39
Fuzzy Rules Extraction from Connectionist Structures....Pages 41-57
Integration of Explicit and Implicit Knowledge in Hybrid Intelligent Systems....Pages 59-69
Practical Implementation Aspects Regarding Real-World Application of Hybrid Intelligent Systems....Pages 71-150
New Trends of Developing Hybrid Intelligent Systems – AIS Hybridization and DNA-Hybridization....Pages 151-161
Genetic Algorithms Based Hybrid Intelligent Systems....Pages 163-194
Back Matter....Pages -
Hybrid Intelligent Systems has become an important research topic in computer science and application field in science and engineering. This book offers a gentle introduction to the engineering aspects of hybrid intelligent systems, also emphasizing the interrelation with the main intelligent technologies such as genetic algorithms – evolutionary computation, neural networks, fuzzy systems, evolvable hardware, DNA computing, artificial immune systems. A unitary whole of theory and application, the book provides readers with the fundamentals, background information, and practical methods for building a hybrid intelligent system. It treats a panoply of applications including many in industry, educational systems, forecasting, financial engineering, and bioinformatics. This volume is useful to newcomers in the field because it quickly familiarizes them with engineering elements of developing hybrid intelligent systems and a wide range of real applications, including non-industrial applications. Researchers, developers and technically oriented managers can use the book for developing both new hybrid intelligent systems approaches and new applications requiring the hybridization of the typical tools and concepts to Computational Intelligence.
Content:
Front Matter....Pages -
Intelligent Techniques and Computational Intelligence....Pages 1-11
Neuro-Fuzzy Based Hybrid Intelligent Systems for Fault Diagnosis....Pages 13-24
Neuro-Fuzzy Integration in Hybrid Intelligent Systems....Pages 25-39
Fuzzy Rules Extraction from Connectionist Structures....Pages 41-57
Integration of Explicit and Implicit Knowledge in Hybrid Intelligent Systems....Pages 59-69
Practical Implementation Aspects Regarding Real-World Application of Hybrid Intelligent Systems....Pages 71-150
New Trends of Developing Hybrid Intelligent Systems – AIS Hybridization and DNA-Hybridization....Pages 151-161
Genetic Algorithms Based Hybrid Intelligent Systems....Pages 163-194
Back Matter....Pages -
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