In this paper a neurocomputing strategy is presented which combines data processing capabilities of neural networks and numerical structural optimization. In this strategy, an improved counterpropagation neural network is used. Two arti"cial neural networks are trained, one for the constraints and t
Reliability-based structural optimization using neural networks and Monte Carlo simulation
β Scribed by Manolis Papadrakakis; Nikos D Lagaros
- Publisher
- Elsevier Science
- Year
- 2002
- Tongue
- English
- Weight
- 183 KB
- Volume
- 191
- Category
- Article
- ISSN
- 0045-7825
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
A new class of artificial neural network based genetic algorithms (ANN-GA) has been developed for reliability analysis of structures. The methods involve the selection of training datasets for establishing an ANN model by the uniform design method, approximation of the limit state function by the tr
To diagnose faults in engineering structures in the situations where the excitation signals are unavailable or inaccessible, response-only data, transmissibility function, are utilised to train neural networks. The technique is verified with two examples based on two different structural systems. Th