Enhancement of speed and efficiency of an internet-based gear design optimisation

Publication Type:

Journal Article

Authors:

Amin, N.; Su, D.

Source:

International Journal of Automotive Technology and Management, Volume 3, Number 3-4, p.279-292 (2003)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-1542475386&partnerID=40&md5=f9c625cf3e95c842d4b1e40b053b855d

Abstract:

An internet-based gear design optimisation program has been developed for geographically dispersed teams to collaborate over the internet. The optimisation program implements genetic algorithm. A novel methodology is presented that improves the speed of execution of the optimisation program by integrating artificial neural networks into the system. The paper also proposes a method that allows an improvement to the performance of the back propagation-learning algorithm. This is done by rescaling the output data patterns to lie slightly below and above the two extreme values of the full range neural activation function. Experimental tests show the reduction of execution time by approximately 50%, as well as an improvement in the training and generalisation errors and the rate of learning of the network.

Copyright© Gerpisa
Concéption Tommaso Pardi
Administration Géry Deffontaines

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