Prediction Model of Annual Precipitation Based on Cloud Model
It is very important for risk management of agricultural drought to predict the precipitation of the future year. According to features of precipitation time-series, prediction rules based on current tendency and the neighbor year are suggested. Each rule is described by cloud model that combines stochastic uncertainty with fuzzy uncertainty and precipitation prediction is taken with uncertain cloud reasoning. Results indicate that annual precipitation prediction with cloud model is good at the mining of uncertain knowledge and can find out more information than traditional methods. In fact, this is a new data mining model for time-series. Any similar problem can be dissolved better by the method, such as runoff prediction, water demand of city prediction and so on. It is significant to spread this method.
annual precipitation prediction time series cloud model neural network grey model
CHEN Xiao-nan DUAN Chun-qing QIU lin HUANG Qiang JIN Yan-guo
College of Water Resources and Hydropower, Xian University of Technology, Xian 710048, China Department of capital, North China Institute of Water Conservancy and Hydroelectric Power, Zhengzhou
国际会议
The 1st International Conference on Risk Analysis and Crisis Response(首届风险分析与危机反应国际学术研讨会)
上海
英文
359-362
2007-09-25（万方平台首次上网日期，不代表论文的发表时间）