الصفحة 1
الصفحة 1
Neural Networks in a Softcomputing Framework
This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model.
Knowledge-Based Intelligent Information and Engineering Systems ; 12th International Conference, KES 2008, Zagreb, Croatia, September 3-5, 2008, Proceedings, Part I
The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems; fuzzy and neuro-fuzzy systems; evolutionary computation; machine learning and classical AI; agent systems; knowledge based and expert systems; intelligent vision and image processing; knowledge management, ontologies, and data mining; Web intelligence, text and multimedia mining and retrieval; and intelligent robotics and control.
Advances in Evolutionary Computing for System Design
Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book includes thirteen chapters covering a wide area of topics in evolutionary computing and applications including: -Introduction to evolutionary computing in system design - Evolutionary neuro-fuzzy systems - Evolution of fuzzy controllers - Genetic algorithms for multi-classifier design -Evolutionary grooming of traffic -Evolutionary particle swarms -Fuzzy logic systems using genetic algorithms - Evolutionary algorithms and immune learning for neural network-based controller design - Distributed problem solving using evolutionary learning -Evolutionary computing within grid environment -Evolutionary game theory in wireless mesh networks - Hybrid multiobjective evolutionary algorithms for the sailor assignment problem - Evolutionary techniques in hardware optimization
