RBF神经网络的汛期旱涝预报方法研究
THE APPLICATION OF RBF NEURAL NETWORK IN FORECASTING THE RAINY SEASON DROUGHT/FLOOD IN FUJIAN
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摘要: 运用福建省25个代表站汛期降水量资料,得到了能够反映全省旱涝状况指标,以此指标为预报量,运用相关分析和逐步回归分析方法,从前期海温场、大气环流场中选取了预报因子,并据此建立了福建汛期旱涝的多元线性回归和RBF神经网络预测模型。结果表明,RBF神经网络模型在历史样本拟合精度上、样本交叉检验和模型的实际预测能力上都明显优于传统的线性回归方法,该模型在实际预测中具有良好的应用能力和推广价值。Abstract: A provincial drought/flood index is constructed on the basis of precipitation data of rainy seasons from 25 representative stations in Fujian province. For the prediction of the index, the multi-line regression model and RBF neural network model (RNNM) are introduced and the series of predictors are selected from previous monthly SST and 500hPa height field data by means of correlation and stepwise regression. The results show that the RNNM is much better than multi - line regression model in terms of the precision of historical sample fittings, the value of sample intercrossing test and actual prediction ability. The model proves to be widely applicable.
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Key words:
- RBF neural network /
- drought and flood in rainy season /
- forecast model
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[1] 张力华.国外人工智能技术在天气预报中的应用综述[J].气象科技,1999(1):1-4. [2] 金龙,陈宁,林振山.基于人工神经网络的集成预报方法研究和比较[J].气象学报,1999,57(2):198-207. [3] 周佩玲,陶小丽,傅忠谦,等.改进RBF神经网络用于降水量预测[J].小型微型计算机,2001,22:244-246. [4] 胡江林,涂松柏,冯光柳.基于人工神经网络的暴雨预报方法探讨[J].热带气象学报,2003,19(4):442-428. [5] 魏凤英.现代气候统计诊断与预测技术[M].北京:气象出版社,1999.187-194. [6] 闻新,周露,王丹力,等.神经网络应用设计[M].北京:科学出版社,2000.245-247. [7] 楼顺天,施阳.给予MTATLAB的系统分析与设计--神经网络[M].西安:西安电子科技大学出版社,2000.14-16. [8] 鞠笑生,杨贤为,陈丽娟,等.我国单站旱涝指标确定和区域旱涝级别划分的研究[J].应用气象学报,1997,8(1):26-33. [9] 章明亮,李燕欣.国内常用旱涝指标的分类研究[J].气象科技,1993(3):81-87.
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