模糊-神经网络模型在长沙汛期逐月降雨量中长期预报中的应用  

Mid-to-long-term forecasting of monthly rainfall in Changsha flood season on fuzzy-neural network

作　　者：易瑾瑜 宋荷花 陈春明 

机构地区：[1]湖南长沙水文局,湖南长沙410010

出　　处：《有色金属文摘》2015年第1期9-12,共4页Nonferrous Metals Abstract

摘　　要：当前长沙汛期降雨特点凸显,做好汛期逐月降雨量预报对长沙防洪减灾、水资源调度工作具有重要价值。首先分析气象资料与预报产品的因果关系,然后再运用模糊数学方法进一步挑选预报因子,最后采用神经网络模型对长沙汛期降雨量进行逐月预报。预报结果显示,60场预报中有51场合格,合格率为85%,预报成果较合理,方法可靠,可作为今后长沙市汛期降雨量中长期预报的基本依据。The rainfall characteristics of current Changsha flood season is displayed, Monthly rainfall forecast has the important value to the flood control and water resources regulation. By analyzing the causes and fuzzy mathematical model and selecting predictors,Monthly rainfall in Changsha was forecasted by using neural network model. Forecast results show that 51 games in 60 forecast are qualified, the qualified rate was 85%, The prediction results is reasonable, the method is reliable. The Forecast results Can be used as a basic reference in mid - to - long - term forecasting of precipitation during flood season.

关 键 词：模糊-神经网络 长沙 汛期 逐月雨量 中长期预报 

分 类 号：P315.7[天文地球—地震学]