广东工业大学学报
廣東工業大學學報
엄동공업대학학보
JOURNAL OF GUANGDONG UNIVERSITY OF TECHNOLOGY
2014年
4期
54-59
,共6页
Bagging%C4.5算法%组合分类器%协同%气温预测
Bagging%C4.5算法%組閤分類器%協同%氣溫預測
Bagging%C4.5산법%조합분류기%협동%기온예측
Bagging%C4.5 algorithm%multi-classifiers%cooperative%air temperature prediction
气象数据挖掘是近年来研究的热点，组合分类器能够实现协同计算以提高效率和准确性，就此本文采用数据挖掘方法中的决策树组合分类器对某地气象进行了气温预测，主要依据C4．5经典算法、Bagging集成方法构建组合决策树，并加入协同的思想建立了预测气温的决策树协同分析模型．实验表明，基于Bagging的决策树协同模型对于局部区域的气温预测具有较高的准确率．
氣象數據挖掘是近年來研究的熱點，組閤分類器能夠實現協同計算以提高效率和準確性，就此本文採用數據挖掘方法中的決策樹組閤分類器對某地氣象進行瞭氣溫預測，主要依據C4．5經典算法、Bagging集成方法構建組閤決策樹，併加入協同的思想建立瞭預測氣溫的決策樹協同分析模型．實驗錶明，基于Bagging的決策樹協同模型對于跼部區域的氣溫預測具有較高的準確率．
기상수거알굴시근년래연구적열점，조합분류기능구실현협동계산이제고효솔화준학성，취차본문채용수거알굴방법중적결책수조합분류기대모지기상진행료기온예측，주요의거C4．5경전산법、Bagging집성방법구건조합결책수，병가입협동적사상건립료예측기온적결책수협동분석모형．실험표명，기우Bagging적결책수협동모형대우국부구역적기온예측구유교고적준학솔．
Meteorological data mining has been a hot research spot recently.Combined classifiers can be used in collaborative computing to improve the efficiency and accuracy.Based on C4.5 classic algorithm and the bagging integrated method, it constructed a cooperative decision tree, and proposed a decision tree model for multi-classifiers to predict the air temperature.Experimental results show that the coopera-tive model for the prediction of local area atmospheric temperature, based on multi-classifiers of the deci-sion tree, has higher accuracy than others.
