代〓旭,陈元芳.基于i Alt NSGA Ⅱ aJG算法的HBV模型参数优化及其应用[J].水电能源科学,2018,36(6):14-16
基于i Alt NSGA Ⅱ aJG算法的HBV模型参数优化及其应用
Application of i Alt NSGA Ⅱ aJG Algorithm in Parameter Optimization of HBV Model
  
DOI:
中文关键词:  HBV模型  参数优化  i NSGA Ⅱ多目标优化算法  NSGA Ⅱ多目标优化算法  i Alt NSGA Ⅱ aJG算法
英文关键词:HBV model  parameter optimization  i NSGA Ⅱ multi objective optimization algorithm  NSGA Ⅱmulti objective optimization algorithm  i Alt NSGA Ⅱ aJG algorithm
基金项目:国家自然科学基金项目(51479061)
作者单位
代〓旭,陈元芳 河海大学 水文水资源学院江苏 南京 210098 
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中文摘要:
      针对种群数量众多且参数率定耗时的问题,对比分析了具有继承性的NSGA Ⅱ(i NSGA Ⅱ)算法与NSGA Ⅱ算法及两者考虑跳跃基因的相关算法的收敛性能,验证了基因继承性对算法性能的提升,从中选出最优算法。利用尼泊尔巴格马蒂河流域2000~2004年实测洪水径流过程资料对HBV模型进行参数率定,得出Pareto最优解,并利用2005年5场洪水日径流过程进行模型检验。结果表明,i NSGA Ⅱ算法优于相对应的NSGA Ⅱ算法,从中选出的最优i Alt NSGA Ⅱ aJG算法能够最快地得到最优解且解的质量较好,表明i Alt NSGA Ⅱ aJG优化算法在解决多参数多目标优化问题中具有优势。
英文摘要:
      Aiming at a large number of populations and time consuming of parameters calibration, the convergence performance of i NSGA II and NSGA II as well as their jumping gene adaptations were compared and analyzed. The gene inheritance to improve algorithm was verified for selecting the best algorithm (i Alt NSGA II aJG). The observed daily discharge data of Marty River Basin in Nepal was used to construct HBV hydrological model, and i Alt NSGA II aJG was adopted to get Pareto optimal solution. The model was tested by using 5 daily floods series in 2005. The results show that the i NSGA II algorithm is superior to NSGA II. The best selected i Alt NSGA II aJG algorithm has the fastest speed for obtaining optimal solutions and its quality is good. It shows that the i Alt NSGA II aJG has the advantage in solving multi parameter and multi objective optimization problems.
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