Computing Network Model for Intelligent Systems: Hybrid of Neural Networks, Multi-knowledge, Fuzzy Logic, Rough Set, and Bayesian Classifier - Qingxiang Wu - Books - VDM Verlag Dr. Müller - 9783639225600 - January 8, 2010
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Computing Network Model for Intelligent Systems: Hybrid of Neural Networks, Multi-knowledge, Fuzzy Logic, Rough Set, and Bayesian Classifier


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Scientists mimicked birds and eventually created airplanes using integration of biological principles and modern science and technology. In recent decades scientists have been trying to simulate intelligence in the brain, in which huge number of neurons forms powerful computing networks to perform intelligent behaviours. This book presented a framework of computing network models for artificial intelligent systems to mimic intelligent behaviours. The models are inspired from some biological principles, and furthermore they have been enhanced using hybrid of current artificial intelligent techniques such as machine learning, neural networks, multi-knowledge, fuzzy logic, rough set, Bayes classifier, and evidence reasoning theory. The key idea of the book is to encourage scientists to take more biological findings to build artificial intelligent systems. More importantly biologically inspired models should be extended to combine current artificial intelligent techniques to achieve high level intelligence in some specific aspects. The book presents a demonstration of the effort in implementation of intelligent behaviours using computing networks.

Media Books     Paperback Book   (Book with soft cover and glued back)
Released January 8, 2010
ISBN13 9783639225600
Publishers VDM Verlag Dr. Müller
Pages 292
Dimensions 150 × 220 × 10 mm   ·   430 g
Language English  

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