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不同优化算法在新安江模型参数率定中的效果评估
作者姓名:石朋  陆美霞  吴洪石  瞿思敏  李紫纯  丁松  王啸  邱超
作者单位:河海大学水文水资源学院,江苏 南京 210098;河海大学水安全与水科学协同创新中心,江苏 南京 210098;浙江省水文管理中心,浙江 杭州 310009
基金项目:国家自然科学基金项目(52179011)
摘    要:In response to the problem of finding a practical, robust, and efficient optimization algorithms in hydrological simulation forecasting and determining the global optimal solution of parameters based on them, the Wucha section, a typical control section in the Qijiang River Basin, was selected as the research object. Four optimization algorithms, GA、 SCE-UA、CMA-ES、PSO, were selected to calibrate the convergence parameters of the distributed Xin’anjiang model. The parameter calibration performance of the algorithm was evaluated from four aspects: effectiveness, stability, time consumption, and efficiency. The results show that CMA-ES algorithm has the best optimization effect and the least time consumption under the same number of iterations. SCE-UA algorithm has the highest stability and efficiency, but its time consumption significantly increases with the increase of iteration times. PSO algorithm has relatively better effectiveness and efficiency, but the stability is the worst. GA algorithm takes relatively less time and has the worst optimization effect and efficiency. The comprehensive property is ranked from best to worst as CMA-ES, SCE-UA, PSO, and GA algorithms. © 2023, Editorial Board of Water Resources Protection. All rights reserved.

关 键 词:分布式新安江模型  参数率定  洪水预报  优化算法  綦江流域
收稿时间:2022-05-30
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