Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.compstruc.2010.05.001
Title: Uniformly sampled genetic algorithm with gradient search for structural identification - Part I: Global search
Authors: Zhang, Z. 
Koh, C.G. 
Duan, W.H.
Keywords: Genetic algorithms
Quasi-random sequence
Sampling methods
Structural identification
Issue Date: Aug-2010
Citation: Zhang, Z., Koh, C.G., Duan, W.H. (2010-08). Uniformly sampled genetic algorithm with gradient search for structural identification - Part I: Global search. Computers and Structures 88 (15-16) : 949-962. ScholarBank@NUS Repository. https://doi.org/10.1016/j.compstruc.2010.05.001
Abstract: This paper is the first of two-part series on a uniformly sampled genetic algorithm with gradient search devised to efficiently solve the optimization-based structural identification. The strategy involves multi-species exploration, adaptive search space reduction and quasi-random sequence sampling. The use of a small number of uniform samples enables preliminary exploration in the solution space so as to shorten the "learning curve" considerably. The proposed strategy is shown by numerical study to give much better identification accuracy than the original search space reduction method, while using much less computational time for identification of known-mass and unknown-mass systems. © 2010 Elsevier Ltd. All rights reserved.
Source Title: Computers and Structures
URI: http://scholarbank.nus.edu.sg/handle/10635/66356
ISSN: 00457949
DOI: 10.1016/j.compstruc.2010.05.001
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