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基于均生函数模型的香屯站年最高水位模拟与预测
引用本文:黄燕,张静怡,顾鹤南. 基于均生函数模型的香屯站年最高水位模拟与预测[J]. 南水北调与水利科技(中英文), 2010, 8(1): 72-74
作者姓名:黄燕  张静怡  顾鹤南
作者单位:河海大学,水文水资源学院,南京,210098
摘    要:对江西乐安河流域香屯站1956年-2005年年最高水位,采用均生函数方法,生成25个周期性基函数,利用SPSS软件进行逐步回归因子挑选,最终筛选出10个周期性基函数作为预测对象的影响因子,建立最优回归方程。结果表明:该模型对非极值的模拟和预测精度很高,对极值的模拟效果较其它模型有很大改善,但仍然是主要误差来源。

关 键 词:均生函数  周期性基函数  SPSS  逐步回归

Simulation and Forecast of Maximum Annual Water Level Based on Model of Average-Growing Function at Xiangtun Station
HUANG Yan,ZHANG Jing-yi,GU He-nan. Simulation and Forecast of Maximum Annual Water Level Based on Model of Average-Growing Function at Xiangtun Station[J]. South-to-North Water Transfers and Water Science & Technology, 2010, 8(1): 72-74
Authors:HUANG Yan  ZHANG Jing-yi  GU He-nan
Abstract:The method of average-growing function was performed with maximum annual water level at Xiangtun station from the year of 1956 to 2005 to create 25 periodic functions. After filtering by stepwise regression factor method employed by SPSS software, the final 10 periodic functions were selected as the impact factors to predict and establish the optimal regression equation. The results showed that the model had a high precision to predict and simulate the non-extreme value. The result of extreme values had significantly improved compared with other models, however, which were still attributed to the main source of error.
Keywords:SPSS  average-growing function  periodic functions  SPSS  stepwise regression
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