Yamashita, Hideo and Cingoski, Vlatko (1994) The Hopfield Neural Network and its Application for direct Solution and inverse Optimization in Finite Element Analysis. Proceedinds of 3rd JapanHungary Joint Seminar on Applied Electromagnetics in Materials and Computational Technology, 38 (3). pp. 231228.

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Abstract
The application of artificial neural network technique and particularly the Hopfield neural network in ordinary finite element analysis is presented. Due to the main property of the Hopfield neural network to minimize the stored network energy, this type of neural network can easily find application in finite element analysis. In this paper two specific applications of the Hopfield neural network will be discussed: First, for obtaining the solution of finite element analysis directly by minimizing the energy of the network  same as minimization of energy functional in ordinary finite element analysis, and second, for obtaining the solution of inverse optimization problems also in connection with element analysis. Some basic mathematical calculus and correlations between neural network energy and energy functional that has to be minimized in finite element analysis are discussed. Some application examples to clarify the main idea are also presented.
Item Type:  Article 

Subjects:  Engineering and Technology > Mechanical engineering 
Divisions:  Faculty of Electrical Engineering 
Depositing User:  Vlatko Cingoski 
Date Deposited:  18 Dec 2012 14:37 
Last Modified:  24 Jun 2013 06:52 
URI:  http://eprints.ugd.edu.mk/id/eprint/3950 
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