✦ LIBER ✦

Artificial neural networks for structural analysis

✍ Scribed by Ronald A. Perez; Kang-Ning Lou

Publisher: Elsevier Science
Year: 1995
Tongue: English
Weight: 668 KB
Volume: 332
Category: Article
ISSN: 0016-0032
DOI: 10.1016/0016-0032(95)00027-5

No coin nor oath required. For personal study only.

✦ Synopsis

In this work we use the continuous Hopfield network and the continuous bidirectional associative memory system (BAM) in order to develop two novel methodsJbr structural analysis. The development of these techniques is based on the analogous relationship that results J?om comparing the eneryy functions of the above two models with that of the structural displacement method (i.e. the so-called stiffness matrix method) and it takes advantage o.1 the fact that classical numerical methods do not have the characteristics of parallel computation that art(ficial neural networks have. Several examples related to structural deJormation are used to illustrate the superiority of the BAM-based neural networks over other traditional numerical methods and the Hopfield model, especially for the case of large dimensional st(ffhess matrices.

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