Optimizing Neural Network Parameters Using Taguchi’s Design of Experiments Approach: An Application for Equivalent Stress Prediction Model of Automobile Chassis-Reference-Cited by-同舟云学术

Optimizing Neural Network Parameters Using Taguchi’s Design of Experiments Approach: An Application for Equivalent Stress Prediction Model of Automobile Chassis

Published:2018-11 Issue:4 Volume:1 Page:381-389
ISSN:2096-4250
Container-title:Automotive Innovation
language:en
Short-container-title:Automot. Innov.

Author:

Patel Tushar M.,Bhatt Nilesh M.

Publisher

Springer Science and Business Media LLC

Subject

Automotive Engineering

Link

http://link.springer.com/article/10.1007/s42154-018-0045-5/fulltext.html

Reference24 articles.

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3. Rao, H.S., Babu, B.R.: Hybrid neural network model for the design of beam subjected to bending and shear. Sadhana 32(5), 577–586 (2007)

4. Gudur, P.P., Dixit, U.S.: A neural network-assisted finite element analysis of cold flat rolling. Eng. Appl. Artif. Intell. 21(1), 43–52 (2008)

5. Castellani, M., Rowlands, H.: Evolutionary artificial neural network design and training for wood veneer classification. Eng. Appl. Artif. Intell. 22(4), 732–741 (2009)

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