Parameter Estimation Algorithm for Storm Intensity Model with Single Return Period Based on Multicellular Gene Expression Programming

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@Article{journals/jcp/PengLYH14,

• title = "Parameter Estimation Algorithm for Storm Intensity Model with Single Return Period Based on Multicellular Gene Expression Programming",
• author = "Yu-zhong Peng and Jie Li and Chang'an Yuan and Baoqin Hu",
• journal = "Journal of Computers",
• year = "2014",
• number = "9",
• volume = "9",
• pages = "2132--2138",
• month = sep,
• keywords = "genetic algorithms, genetic programming, gene expression programming, Storm rainfall intensity, parameter estimation",
• bibdate = "2014-09-03",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/jcp/jcp9.html#PengLYH14",
• URL = "http://dx.doi.org/10.4304/jcp.9.9.2132-2138",
• abstract = "To resolve the difficulty of parameter estimation of Storm rainfall intensity formulation, a new multicellular GEP parameter estimation algorithm, named MC_GEP_MPO, with a novel individual coding scheme based on Gene Expression Programming algorithm is proposed in this paper. MC_GEP_MPO is used for solving the parameter estimation problem of the single return period of rainfall intensity forecast model using historical rainfall statistical data as a learning example. And its effectiveness in real compute instance has been evaluated. The compared experiment result shows that the proposed method exploring for parameter estimation of Storm rainfall intensity formulation is feasible and precise.",

}

Genetic Programming entries for Yu-zhong Peng Jie Li Chang-an Yuan Baoqin Hu

Citations