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A NOVEL MEANS OF APPLYING NEURAL NETWORKS TO OPTIMIZE THE MULTIRESPONSE PROBLEM · Study

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ArticleA NOVEL MEANS OF APPLYING NEURAL NETWORKS TO OPTIMIZE THE MULTIRESPONSE PROBLEM

Lee‐Ing Tong2001

Article2001

A NOVEL MEANS OF APPLYING NEURAL NETWORKS TO OPTIMIZE THE MULTIRESPONSE PROBLEM

Lee‐Ing Tong · Kun-Lin Hsieh

41 citations·0/0 files stored·Quality Engineering

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Optimal Experimental Design Methods Neural Networks and Applications Advanced Multi-Objective Optimization Algorithms

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Key Words: Experimental designMultiresponseArtificial neural networkOptimizationBackpropagationPrediction.

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References

1980Simultaneous Optimization of Several Response Variables 1981Simultaneous Optimization of Multiple Responses Represented by Polynomial Regression Functions 1996Modified Desirability Functions for Multiple Response Optimization 1993STRATEGIES FOR ROBUST MULTIRESPONSE QUALITY ENGINEERING 1997OPTIMIZING MULTI-RESPONSE PROBLEMS IN THE TAGUCHI METHOD BY FUZZY MULTIPLE ATTRIBUTE DECISION MAKING 1988Characterizing and optimizing multi‐response processes by the taguchi method 1996A PRAGMATIC APPROACH TO MULTIPLE-RESPONSE PROBLEMS USING LOSS FUNCTIONS

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2009Comparison of performances of five prospective approaches for the multi-response optimization 2005A New Approach for Multiple-Response Optimization

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Details

Year2001

Typearticle

Published2001-02-01

VenueQuality Engineering

ISSN-L0898-2112

Languageen

Citations41

Files0 public / 0

ShelfOptimal Experimental Design Methods

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doi10.1080/08982110108918619

openalex_workW2083747351

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