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Computational Intelligence Techniques for New Product Design

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Cover of 'Computational Intelligence Techniques for New Product Design'

Table of Contents

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    Book Overview
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    Chapter 1 Computational Intelligence Techniques for New Product Design
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    Chapter 2 Computational Intelligence Technologies for Product Design
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    Chapter 3 Determination of Importance of Customer Requirements Using the Fuzzy AHP Method
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    Chapter 4 An Enhanced Fuzzy AHP Method with Extent Analysis for Determining Importance of Customer Requirements
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    Chapter 5 Development of Product Design Models Using Classical Evolutionary Programming
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    Chapter 6 Development of Product Design Models Using Fuzzy Regression Based Genetic Programming
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    Chapter 7 Generalized Fuzzy Least Square Regression for Generating Customer Satisfaction Models
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    Chapter 8 An Enhanced Neuro-fuzzy Approach for Generating Customer Satisfaction Models
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    Chapter 9 Optimization of Customer Satisfaction Using an Improved Simulation Annealing
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    Chapter 10 An Enhanced Genetic Algorithm Integrated with Orthogonal Design
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    Chapter 11 A Nonlinear Fuzzy Regression for Developing Manufacturing Process Models
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    Chapter 12 Rule Extraction from Experimental Data for Manufacturing Process Design
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    Chapter 13 Conclusion and Future Work
Attention for Chapter 11: A Nonlinear Fuzzy Regression for Developing Manufacturing Process Models
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Chapter title
A Nonlinear Fuzzy Regression for Developing Manufacturing Process Models
Chapter number 11
Book title
Computational Intelligence Techniques for New Product Design
Published by
Springer, Berlin, Heidelberg, January 2012
DOI 10.1007/978-3-642-27476-3_11
Book ISBNs
978-3-64-227475-6, 978-3-64-227476-3
Authors

Kit Yan Chan, C. K. Kwong, Tharam S. Dillon

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