首页 | 本学科首页   官方微博 | 高级检索  
     

年径流预测的Shepard插值模型
引用本文:金菊良,魏一鸣,丁晶,付强.年径流预测的Shepard插值模型[J].长江科学院院报,2002,19(1):52-55.
作者姓名:金菊良  魏一鸣  丁晶  付强
作者单位:1. 合肥工业大学 土建学院,安徽,合肥,230009
2. 中国科学院,科技政策与管理科学研究所,北京,100080
3. 四川大学,水电学院,四川,成都,610065
基金项目:国家自然科学基金委员会-水利部长江水利委员会联合资助项目,国家自然科学基金,50099620,49871018,,
摘    要: 年径流现象是多种因子综合作用的结果,各预测因子与年径流之间是复杂的非线性关系。目前提出的年径流预测模型大多用显式函数来表示,其具体的函数形式需随研究地区的不同而作相应的改变,求解这些函数一般较复杂。实际预测工作则常常是把本次年径流的预测因子值与当地年径流预测因子历史样本系列逐个进行比较分析,实践表明这种方法行之有效。为此,提出用Shepard插值方法构建年径流预测的新模型(SP模型)。实例研究的结果说明,SP模型简便、实用性强,可在径流中长期预测中广泛应用。

关 键 词:年径流  Shepard插值  非线性预测  遗传算法
文章编号:1001-5485(2002)01-0052-04

Shepard interpolation model for predicting annual runoff
JIN Ju liang ,WEI Yi ming ,DING Jing ,FU Qiang.Shepard interpolation model for predicting annual runoff[J].Journal of Yangtze River Scientific Research Institute,2002,19(1):52-55.
Authors:JIN Ju liang  WEI Yi ming  DING Jing  FU Qiang
Affiliation:JIN Ju liang 1,WEI Yi ming 2,DING Jing 3,FU Qiang 3
Abstract:Predicting annual runoff is very important for guiding the management of water resources. Annual runoff is a result caused by many factors, and the relations of annual runoff and the predicting factors are complex and nonlinear. Nowadays the annual runoff prediction models mostly express the relations by explicit functions, the expressions of the functions will be changed according to the studying areas, and it is very difficult to resolve the functions. Predicting results in practice are generally obtained by comparing the predicting factors values of the current annual runoff with the sample series of the history annual runoff in the same area, which is proved to be very feasible and effective by a lot of practices. For this reason, a new model for predicting annual runoff, named SP model, is presented based on Shepard interpolation technique. The case study shows that SP model is convenient and effective, and that SP model can be applied to mid and long term prediction of many runoff processes.
Keywords:annual runoff  Shepard interpolation technique  nonlinear prediction  genetic algorithm
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《长江科学院院报》浏览原始摘要信息
点击此处可从《长江科学院院报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号