The Calibration on Nonlinear Single Return Period Storm Intensity Model Parameters by the New Blending Accelerating Genetic Algorithm

被引:0
作者
Ren, Bozhi [1 ]
Lu, Jingcheng [1 ]
Zhou, Hongtao [1 ]
机构
[1] Hunan Univ Sci & Technol, Fac Civil Engn, Xiangtan 411201, Peoples R China
来源
PROGRESS IN INDUSTRIAL AND CIVIL ENGINEERING, PTS. 1-5 | 2012年 / 204-208卷
关键词
Storm intensity models; Blending genetic algorithm; Parameter optimization; CROSSOVER OPERATOR;
D O I
10.4028/www.scientific.net/AMM.204-208.3480
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Through improving the real-coded genetic algorithms and embedding the algorithm of accelerating the local search in the Powell direction and the operation of accelerating cycle, thereby it is constructed the New blend Accelerating Genetic Algorithm (hereinafter referred to as NBAGA). The applied examples of the calibration on nonlinear single return period storm intensity model parameters show that this method takes into account of the advantages of both the advantages of the improved real-coded genetic algorithms and the Powell Algorithm, therefore this method is an excellent nonlinear optimization method which can search the global optimal exact solutions quickly and in greater probability, as well as doing subtle search locally.
引用
收藏
页码:3480 / 3487
页数:8
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