基于C4.5算法的長江中下游地區(qū)夏季降水預(yù)測模型研究及應(yīng)用

doi:10.3969/2016jms.0052

首頁 > 過刊瀏覽>2017年第37卷第2期 >256-264. DOI:10.3969/2016jms.0052

基于C4.5算法的長江中下游地區(qū)夏季降水預(yù)測模型研究及應(yīng)用
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                        10.3969/2016jms.0052
                    
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基金項目:國家科技支撐計劃項目（2012BAH05B01）；公益性行業(yè)（氣象）科研專項（GYHY201206068）；國家自然科學(xué)基金面上資助項目（41276033）；江蘇省科技支撐計劃項目（BE2012774，BE2014729）；江蘇高校優(yōu)秀學(xué)科建設(shè)工程項目（PAPD）

Research and application of summer rainfall prediction model in the middle and lower reaches of the Yangtze River based on C4.5 algorithm

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為了對長江中下游夏季降水進行短期氣候預(yù)測，利用國家氣候中心提供的74項環(huán)流指數(shù)和NOAA整編的西太平洋型WP指數(shù)、MEI指數(shù)、ENSO指數(shù)等多種全球環(huán)流指數(shù)資料，歸納整理了影響長江中下游夏季降水的34個前期春季因子，討論了前期春季因子與夏季降水的關(guān)系，并利用這34個前期春季因子通過數(shù)據(jù)挖掘中的C4.5算法對1951-2013年（63 a）長江中下游夏季降水，建立判別降水偏多以及偏少的兩類決策樹預(yù)測模型，并分別得到5條和7條綜合判別規(guī)則。隨機選取80%左右歷史年份數(shù)據(jù)作為模型的訓(xùn)練集，兩模型的訓(xùn)練集準確率分別為94.12%和93.88%，剩余20%年份數(shù)據(jù)作為模型測試集，模型的測試預(yù)測準確率分別達91.67%和85.71%。模型預(yù)測應(yīng)用也顯示結(jié)果正確。模型研究和應(yīng)用顯示，基于C4.5算法的長江中下游夏季降水預(yù)測模型具有較高的預(yù)測準確率，模型構(gòu)建合理有效，判別規(guī)則依據(jù)大數(shù)據(jù)理論，廣泛考慮相關(guān)因子以及因子的排列組合，智能化選擇關(guān)鍵因子，易于客觀化、自動化實施，為長江流域汛期降水的短期氣候預(yù)測提供了新的思路與方法。

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In order to conduct the short-term climate prediction on summer precipitation in the middle and lower reaches of the Yangtze River, 74 circulation index data from National Climate Center and then global circulation index data such as the Western Pacific (WP) index, Multivariate ENSO Index(MEI), ENSO index and so on from NOAA were used to sum up 34 early spring factors affecting the summer precipitation in the middle and lower reaches of the Yangtze River and to analyze the relationship between early spring factors and summer rainfall. Furthermore, two kinds of summer rainfall decision tree prediction models are constructed for the middle and lower reaches of the Yangtze River during 1951-2013 based on the C4.5 algorithm of data mining. Five discriminant rules for "whether too much" and seven discriminant rules for "whether too little" were obtained. In whole data, about 80% history data are randomly selected as training set for the models with the training set accuracy of 94.12% and 93.88%, respectively. The remaining 20% data are used as the test set for the models with the prediction accuracy of 91.67% and 85.71% respectively. Results show that the summer rainfall prediction models in the middle and lower reaches of the Yangtze River based on C4.5 algorithm have higher prediction accuracy with reasonable and effective models construction. The models' discriminant rules are based on large data theory, and consider a wide range of related factors and factor permutation and combination. The models are processed by intelligent selection of key factors, and objective and automatic implement is good enough to provide a new idea and method for the short-term climate prediction on precipitation in flood season of the Yangtze River Basin.

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苗春生,何東坡,王堅紅,史達偉.基于C4.5算法的長江中下游地區(qū)夏季降水預(yù)測模型研究及應(yīng)用.氣象科學(xué),2017,37(2):256-264 MIAO Chunsheng, HE Dongpo, WANG Jianhong, SHI Dawei. Research and application of summer rainfall prediction model in the middle and lower reaches of the Yangtze River based on C4.5 algorithm. Journal of the Meteorological Sciences,2017,37(2):256-264

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收稿日期:2016-01-25
最后修改日期:2016-03-28
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在線發(fā)布日期: 2017-05-16
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