Mircea Gh. Negoita, Daniel Neagu, Vasile Palade

Computational Intelligence

Engineering of Hybrid Systems

• Gebundenes Buch

Produktbeschreibung

Hybrid Intelligent Systems has become an important research topic in computer science and a key 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.

Produktdetails

• Studies in Fuzziness and Soft Computing 174
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-540-23219-3
• Seitenzahl: 213
• Englisch
• Abmessung: 235mm
• Gewicht: 470g
• ISBN-13: 9783540232193
• ISBN-10: 3540232192
• Artikelnr.: 13926680

Autorenporträt

Mircea Negoita, Centre for Computational Intelligence, Wellington Institute of Technology, Wellington, New Zealand / Daniel Neagu, University of Bradford, West Yorkshire, UK / Vasile Palade, University of Oxford, UK

Inhaltsangabe

Intelligent Techniques and Computational Intelligence.- Neuro-Fuzzy based Intelligent Hybrid Systems for Fault Diagnosis.- Neuro-Fuzzy Integration in Intelligent Hybrid Systems.- Fuzzy Rules Extraction from ANNs.- Integration of Explicit and Implicit Knowledge in Intelligent Hybrid Systems.- Practical Implementation Aspects Regarding Real-World Applications of Intelligent Hybrid Systems (NEIKeS, WITNEeSS and other original applications).- New Trends of Developing Intelligent Hybrid Systems - AIS Hybridization and DNA Hybridization.- Genetic Algorithms Based Intelligent Hybrid Systems.