Journal of Guangdong University of Technology ›› 2014, Vol. 31 ›› Issue (4): 54-59.doi: 10.3969/j.issn.1007-7162.2014.04.010

• Comprehensive Studies • Previous Articles     Next Articles

Prediction of  Atmospheric Temperature Based on Multi-classifiers of Decision Tree

Li Jun-lei, Teng Shao-hua, Zhang Wei   

  1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2014-04-16 Online:2014-12-28 Published:2014-12-28

Abstract: 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 cooperative model for the prediction of local area atmospheric temperature, based on multi-classifiers of the decision tree, has higher accuracy than others.

Key words: Bagging; C4.5 algorithm; multi-classifiers; cooperative; air temperature prediction

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