检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:谭炳卿[1]
机构地区:[1]水利部淮河水利委员会
出 处:《水文》1996年第5期8-14,共7页Journal of China Hydrology
摘 要:模型参数的识别是模型研制与应用成功与否的关键。介绍了三个自动优选模型参数的方法,以新安江模型为例,应用14个流域的资料,对罗森布郎克(Rosenbrock)法、改进的单纯形(Simplex)法和基因(Genetic)算法优选模型参数的效果,优化方法的收敛速度及参数初值对优选效果的影响进行了比较分析,初步分析了基因法参数l和IMAX对优选结果的影响,指出以基因法的优选结果作为参数初值,再用其它两种方法进一步优化,是模型参数识别的一个有效途径。The successful development and application of a conceptual rainfall-runoff model depends mainly on how well it is calibrated. This paper introduces three optimization methods, namely Rosenbrock, Simplex and Genetic algorithm, for automatic calibration of the hydrological models, The performances of the methods were analyzed on the basis of the application of them to the Xinanjiang model using 14 catchments data. The effects of the parameter values of the Genetic method on calibration of the model parameter values were preliminarily investigated. The results suggest that the Genetic algorithm with further tuning by other two methods can provide an efficient and robust means for calibrating the conceptual rainfall-runoff models.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.38