For many optimum design problems, the objectiยฎe function is the result of a complex numerical code and may not be differentiable and explicit. The first aim is to propose a way of solยฎing such complexity on an example problem. A noยฎel and global strategy inยฎolยฎing artificial neural networks and a ge
Modelling of structural response and optimization of structural control system using neural network and genetic algorithm
โ Scribed by Li, Q. S. ;Liu, D. K. ;Leung, A. Y. T. ;Zhang, N. ;Tam, C. M. ;Yang, L. F.
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 151 KB
- Volume
- 9
- Category
- Article
- ISSN
- 1062-8002
No coin nor oath required. For personal study only.
โฆ Synopsis
This paper proposes an integrated approach to the modelling and optimization of structural control systems in tall buildings. In this approach, an artificial neural network is applied to model the structural dynamic responses of tall buildings subjected to strong earthquakes, and a genetic algorithm is used to optimize the design problem of structural control systems, which constitutes a mixed-discrete, nonlinear and multi-modal optimization problem. The neural network model of the structural dynamic response analysis is included in the genetic algorithm and is used as a module of the structural analysis to estimate the dynamic responses of tall buildings. A numerical example is presented in which the general regression neural network is used to model the structural response analysis. The modelling method, procedure and the numerical results are discussed. Two Los Angeles earthquake records are adopted as earthquake excitations.
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