Please use this identifier to cite or link to this item:
|Title:||Uniformly sampled genetic algorithm with gradient search for structural identification - Part II: Local search||Authors:||Zhang, Z.
|Issue Date:||Oct-2010||Citation:||Zhang, Z., Koh, C.G., Duan, W.H. (2010-10). Uniformly sampled genetic algorithm with gradient search for structural identification - Part II: Local search. Computers and Structures 88 (19-20) : 1149-1161. ScholarBank@NUS Repository. https://doi.org/10.1016/j.compstruc.2010.07.004||Abstract:||This paper investigates several gradient local search methods as an enhancement to Part I, to further improve the computational efficiency while achieving the same identification accuracy. The present study is significant in several ways. First, this study reveals the characteristics of structural identification from the optimization perspective. Second, the "switch point" from global search to local search is determined with due consideration in convergence speed and avoidance of local optima. Finally, the combined strategy based on Part I and Part II with a particular local search (BFGS) is found to achieve substantial improvement in identification efficiency and accuracy. © 2010 Published by Elsevier Ltd. All rights reserved.||Source Title:||Computers and Structures||URI:||http://scholarbank.nus.edu.sg/handle/10635/66357||ISSN:||00457949||DOI:||10.1016/j.compstruc.2010.07.004|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jun 17, 2019
WEB OF SCIENCETM
checked on Jun 10, 2019
checked on May 24, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.