基于BP和Elman神经网络的福建省汛期旱涝预测模型  

Forecast Models for Fujian Rainy Season Drought/FloodBased on BP and Elman Neural Networks

作　　者：王艳姣[1] 邓自旺[1] 王耀庭[1] 宋德众 

机构地区：[1]南京师范大学地理科学学院 [2]福建省专业气象台,福建福州350001

出　　处：《南京气象学院学报》2004年第6期776-783,共8页Journal of Nanjing Institute of Meteorology

基　　金：国家科技部项目(2001DIB20116);南京气象学院气象灾害和环境变化重点实验室开放课题(KJS02108)

摘　　要：建立了福建汛期旱涝BP和Elman神经网络预测模型,并对两种模型的性能和差异进行了比较,结果表明:动量BP网络模型,特别是具有局部反馈特性的Elman网络模型具有较好的拟合精度和预报效果。此外两种模型对旱涝等级为2和4的预测偏差较大,而对旱涝等级为3的预测较为准确。The forecasting models of momentum BP (MBP) and Elman neural networks are developed for Fujian rainy season drought/flood prediction,and the abilities and differences of the two types of models are compared.Results suggest that the forecasting model of MBP,especially the Elman neural network which has the character of local feedback,have better fitting precision and forecast accuracy.Additionally the forecasting abilities of the two kinds of models are worse for the drought/flood grades of 2 and 4,but best for the drought/flood grades of 3.

关 键 词：动量BP神经网络 ELMAN神经网络 汛期旱涝 预测模型 

分 类 号：P338[天文地球—水文科学]