Computational Intelligence Engineering of Hybrid Systems /

• Κύριοι συγγραφείς: Negoita, Mircea Gh (Συγγραφέας), Neagu, Daniel (Συγγραφέας), Palade, Vasile (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
• Σειρά: Studies in Fuzziness and Soft Computing, 174
• Θέματα: Computer science.; Operations research.; Decision making.; Computers.; Artificial intelligence.; Bioinformatics.; Applied mathematics.; Engineering mathematics.; Computer Science.; Theory of Computation.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).; Applications of Mathematics.; Operation Research/Decision Theory.

 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. 

 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.