Abstract: For engineering planning and design, a paradigm of intelligent fuzzy networks is proposed which consists of fuzzy systems composed of inputs, states, and outputs. Each of the fuzzy systems can be replaced by a neural network, fuzzy confluence rule, fuzzy identifier, and so on, which can learn given knowledge or experience by determining their weighting factors and/or coefficients. After learning, intelligent fuzzy networks have intelligent functions such as evaluation, optimization, and decision-making.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Publication Year: 2003
Publication Date: 2003-01-02
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 1
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