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

Mediji Grāmatas     Paperback Book   (Grāmata ar mīksto vāku un līmēto muguru)
Izlaists 2010. gada 8. janvāris
ISBN13 9783639225600
Izdevēji VDM Verlag Dr. Müller
Lapas 292
Izmēri 150 × 220 × 10 mm   ·   430 g
Valoda Angļu  

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