In this paper, a new method of finite element model updating using neural networks is presented. Many previous model updating techniques have exhibited inconsistent performance when subjected to noisy experimental data. From this background it is clear that a successful model updating method must be
ON MODEL UPDATING USING NEURAL NETWORKS
โ Scribed by M.J. Atalla; D.J. Inman
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 340 KB
- Volume
- 12
- Category
- Article
- ISSN
- 0888-3270
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
One unique feature of neural networks is that they have to be trained to function. In developing an iterative neural network technique for model updating of structures, it has been shown that the number of training samples required increases exponentially as the number of parameters to be updated in
This paper compares various techniques of measuring the generalization ability of a neural network used for model-updating purposes. An appropriate metric for measuring generalization ability is suggested, and it is used to investigate and compare various neural network architectures and training al
In dealing with human nervous system, the sensation of pain is as sophisticated as other physiological phenomena. To obtain an acceptable model of the pain, physiology of the pain has been analysed in the present paper. Pain mechanisms are explained in block diagram representation form. Because of t