| A NEW GENETIC SIMULATED ANNEALING ALGORITHM FOR FLOOD ROUTING MODEL |
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| 作者姓名： | KANGLing WANGCheng JIANGTie-bing |
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| 作者单位： | CollegeofHydropowerandInformationEngineering,HuazhongUniversityofScienceandTechnology,Wuhan430074,China,e-mail,lkaung@hotmail,corn |
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| 摘 要： | In this paper, a new approach, the Genetic Simulated Annealing (GSA), was proposed for optimizing the parameters in the Muskingum routing model. By integrating the simulated annealing method into the genetic algorithm, the hybrid method could avoid some troubles of traditional meth ods, such as arduous trial and error procedure, premature convergence in genetic algorithm and search blindness in simulated annealing. The principle and implementing procedure of this algorithm were described. Numerical experiments show that the GSA can adjust the optimization population, prevent premature convergence and seek the global optimal result. Applications to the Nanyunhe River and Qingjiang River show that the proposed approach is of higher forecast accuracy and practicability.
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| 关 键 词： | 洪水流 参数优化 Muskingum模型 水力机械 遗传模拟算法 韧化 |
A NEW GENETIC SIMULATED ANNEALING ALGORITHM FOR FLOOD ROUTING MODEL |
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| KANGLing WANGCheng JIANGTie-bing.A NEW GENETIC SIMULATED ANNEALING ALGORITHM FOR FLOOD ROUTING MODEL[J].Journal of Hydrodynamics,2004,16(2):233-239. |
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| Authors: | KANG Ling WANG Cheng JIANG Tie-bing College of Hydropower and Information Engineering Huazhong University of Science and Technology Wuhan China |
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| Affiliation: | KANG Ling,WANG Cheng,JIANG Tie-bing College of Hydropower and Information Engineering,Huazhong University of Science and Technology,Wuhan 430074,China |
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| Abstract: | In this paper, a new approach, the Genetic Simulated Annealing (GSA), was proposed for optimizing the parameters in the Muskingum routing model. By integrating the simulated annealing method into the genetic algorithm, the hybrid method could avoid some troubles of traditional methods, such as arduous trial-and-error procedure, premature convergence in genetic algorithm and search blindness in simulated annealing. The principle and implementing procedure of this algorithm were described. Numerical experiments show that the GSA can adjust the optimization population, prevent premature convergence and seek the global optimal result. Applications to the Nanyunhe River and Qingjiang River show that the proposed approach is of higher forecast accuracy and practicability. |
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| Keywords: | Flood routing Genetic Simulated Annealing (GSA) Muskingum model |
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