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《Journal of Nanjing Institute of Meteorology》 2004-06
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Forecast Models for Fujian Rainy Season Drought/FloodBased on BP and Elman Neural Networks

WANG Yan-jiao~(1,2),DENG Zi-wang~2,WANG Yao-ting~1,SONG De-zhong~3(1.School of Geographical Science,Nanjing Normal University,Nanjing210097,China;UIST,Nanjing210044,China;3.Special Observatory of Fujian Province,Fuzhou350001,China)  
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.
【Fund】: 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)
【CateGory Index】: P338
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