Neuro-fuzzy and genetic algorithm in multiple response optimization

Neuro-fuzzy and genetic algorithm in multiple response optimization

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Article ID: iaor2004767
Country: United Kingdom
Volume: 44
Issue: 12
Start Page Number: 1503
End Page Number: 1514
Publication Date: Dec 2002
Journal: Computers & Mathematics with Applications
Authors: , ,
Keywords: programming: network
Abstract:

Optimization of a multiple output system, whose function is only approximately known and is represented in tabular form, is modeled and optimized by the combined use of a neuro-fuzzy network and optimization techniques which do not require the explicit representation of the function. Neuro-fuzzy network is useful for learning the approximate original tabular system. However, the results obtained by the neuro-fuzzy network are represented implicitly in the network. The MANFIS neuro-fuzzy network, which is an extension of the ANFIS network, is used to model the multiple output system and a genetic algorithm issued to optimise the resulting multiple objective decision making problem. A chemical process whose function is represented approximately in tabular form is solved to illustrate the approach.

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