投稿中心

审稿中心

编辑中心

期刊出版

网站地图

友情链接

引用本文:李致家,孔祥光.洪水预报中特征值预报的若干数学方法比较.湖泊科学,1997,9(2):117-122. DOI:10.18307/1997.0204
Li Zhijia,Kong Xiangguang.Comparison on Three Mathematical Models For Special Values in Flood Forecasting. J. Lake Sci.1997,9(2):117-122. DOI:10.18307/1997.0204
【打印本页】   【HTML】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 4187次   下载 2649 本文二维码信息
码上扫一扫!
分享到: 微信 更多
洪水预报中特征值预报的若干数学方法比较
李致家1, 孔祥光2
1.河海大学水资源水文系, 南京 210024;2.沂沭泗水利管理局, 徐州 221009
摘要:
讨论研究了水文特征值预报的数学方法:统计回归模型、神经网络模型和模糊回归模型.三个计算实例表明如果系统的线性关系较好,统计回归模型的结果最好;如果系统的线性关系差,神经网络模型的结果最好;如果用于率定模型的资料太短.任何一个模型都不可靠.
关键词:  洪水预报  神经网络方法  回归分析  模糊回归
DOI:10.18307/1997.0204
分类号:
基金项目:
Comparison on Three Mathematical Models For Special Values in Flood Forecasting
Li Zhijia1, Kong Xiangguang2
1.Department of Water Resoures & Hydrology, Hohai University, Nanjing 210024;2.Yishusi Civil Engineering Bureau, Ministry of Water Resources, Xuzhou 221009
Abstract:
Three mathematical models, i. e. regressive analysts method, artificial neutral method and fuzzy regressive method, are commonly used in the flood forecasting for special values. The practical calculation results of three cases provided in this paper show that either one is suitable for all cases. The regressive analysis method is favorable when the system has better linear correlations; otherwise the artificial neutral net method is better if the system is not linearly correlated. None of the above-mentioned method is reliable when the data needed for the calibration are not enough.
Key words:  Flood forecasting  artificial neutral method  regressive analysis  fuzzy regressive analysis
分享按钮