Title :
A cooperative multi-classifier method for local area meteorological data mining
Author :
Shaohua Teng ; Jihui Fan ; Haibin Zhu ; Wei Zhang ; Dongning Liu ; Xiao Chen ; Xiufen Fu
Author_Institution :
Sch. of Comput. Sci. & Technol., Guangdong Univ. of Technol., Guangzhou, China
Abstract :
Natural disasters can lead to severe losses in human life and property. Because many factors combine in a disaster, such events are difficult to forecast accurately. A cooperative multi-classifier method is proposed in this paper to mine local area meteorological data. The proposed method is verified by the implementation of both base and integration classifiers. Experimental results indicate that our proposed method has higher classification accuracy and faster grouping ability compared with conventional classifiers.
Keywords :
data mining; disasters; geophysics computing; meteorology; pattern classification; base classifier; cooperative multiclassifier method; integration classifier; local area meteorological data mining; natural disasters; Accuracy; Classification algorithms; Data mining; Testing; Training; Weather forecasting; K-Nearest Neighbor algorithm; base classifier; cooperation; data mining; local area meteorological data; multi-classifier;
Conference_Titel :
Computer Supported Cooperative Work in Design (CSCWD), Proceedings of the 2014 IEEE 18th International Conference on
Conference_Location :
Hsinchu
DOI :
10.1109/CSCWD.2014.6846884