Integration of technique for order preference by similarity to ideal solution and back-propagation neural network/genetic algorithm to optimise light guide plate surface roughness process parameters-Reference-Cited by-同舟云学术

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Integration of technique for order preference by similarity to ideal solution and back-propagation neural network/genetic algorithm to optimise light guide plate surface roughness process parameters

Published:2015-11 Issue:sup9 Volume:19 Page:S9-50-S9-54
ISSN:1432-8917
Container-title:Materials Research Innovations
language:en
Short-container-title:Materials Research Innovations

Author:

Wang S. T.¹,Li M. H.²,Lin W. T.³

Affiliation:

1. Department of Commerce Automation and ManagementNational Pingtung University, Taiwan, R.O.C.

2. Department of Industrial Engineering and ManagementNational Quemoy University, Taiwan, R.O.C.

3. Department of Industrial Engineering and ManagementNational Chin-Yi University of Technology, Taiwan, R.O.C.

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science

Link

https://www.tandfonline.com/doi/pdf/10.1179/1432891715Z.0000000001917

Reference18 articles.

1. Simple liquid crystal display backlight unit comprising only a single-sheet micropatterned polydimethylsiloxane (PDMS) light-guide plate

2. Design of a Highly-Efficient Light Guide Plate for the Edge Lighting Backlight Module

3. Determination of Optimal Pulse Metal Inert Gas Welding Parameters with a Neuro-GA Technique

4. Parameter identification of superplastic constitutive model based on heteroscedastic maximum likelihood estimator

5. An efficient and practical approach to obtain a better optimum solution for structural optimization

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