NEURAL NETWORKS FOR COMPUTING IN THE ELASTOPLASTIC ANALYSIS OF STRUCTURES

被引：13
|
作者：
AVDELAS, AV
PANAGIOTOPOULOS, PD
KORTESIS, S
机构：
[1] RHEIN WESTFAL TH AACHEN,DEPT TECH,W-5100 AACHEN,GERMANY
[2] UNIV THESSALONIKI,DEPT COMP SCI,GR-54006 THESSALONIKI,GREECE
来源：
MECCANICA | 1995年 / 30卷 / 01期
关键词：
NEURAL NETWORK; QUADRATIC PROGRAMMING; ELASTOPLASTIC ANALYSIS;
D O I：
10.1007/BF00987122
中图分类号：
O3 [力学];
学科分类号：
08 ; 0801 ;
摘要：
A neural network model is proposed and studied for the treatment of elastoplastic analysis problems. These problems are formulated as Q.P.P.s with inequality subsidiary conditions. In order to treat these conditions the Hopfield model is appropriately generalized and a neural model is proposed covering the case of inequalities. Finally, the parameter identification problem is formulated as a supervised learning problem Numerical applications close the presentation of the theory and the advantages of the neural network approach are illustrated.
引用
收藏
页码：1 / 15
页数：15
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