Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13876
Title: Large-scale structural identification by multi-civilization genetic algorithm approach
Authors: WU LIPENG
Keywords: System Identification; Genetic Algorithms; Local Search; Parallel Genetic Algorithm;
Issue Date: 17-May-2004
Source: WU LIPENG (2004-05-17). Large-scale structural identification by multi-civilization genetic algorithm approach. ScholarBank@NUS Repository.
Abstract: In recent years, the use of genetic algorithms (GA) has shown great potential for parameter identification of complex systems owing to its many inherent advantages. Compared with calculus-based identification methods, the GA method has no requirement for as gradients or derivatives. Furthermore, the method is relatively robust with respect to initial guess and incomplete measurements with noise. Nevertheless, for large systems involving many degrees of freedom and unknown parameters, the computational effort required by the GA approach may still be prohibitive. Furthermore, sequential GA depends on a single population and may not have sufficient diversity to converge to the global optimal solution. In this study, the high concurrency of GA is exploited and parallel GA is developed for structural identification, leading to a??multi-civilizationa?? GA approach. For implementation, a JAVA-based distributed computing approach is adopted to expedite the computation. Numerical experiments are conducted to demonstrate the feasibility and performance of the proposed method.
URI: http://scholarbank.nus.edu.sg/handle/10635/13876
Appears in Collections:Master's Theses (Open)

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