摘要
提出了一种模糊优选神经网络模型与地理信息系统(GIS)相结合的流域面雨量预测方法.利用GIS软件对流域点雨量进行了空间分析,作为模糊优选神经网络的期望输出对网络进行训练,从而在流域面雨量与各站点观测雨量之间建立映射关系.新的点雨量观测数据输入训练好的网络,即可快捷得到本次降雨流域面雨量.
A good areal rainfall calculation means we can forecast flood more accurately and in time.Here,we propose an areal rainfall forecasting methodology integrated fuzzy optimized neural network with Geography Information System(GIS)methods.GIS has advantage of process spatial information.Using many models and methods provided by GIS software,we obtain more accurate areal rainfalls of a catchment.Then,these outputs of the GIS software are taken as the expected output of the fuzzy optimized neural network,and the...
出处
《北京工业大学学报》
CAS
CSCD
北大核心
2009年第2期162-167,共6页
Journal of Beijing University of Technology
基金
国家自然科学基金资助项目(50779005)
水利部科技创新基金资助项目(SCXC2005-01)．
关键词
模糊优选神经网络
地理信息系统
流域面雨量预测
fuzzy optimal neural network
geography information system
areal rainfallforecast
