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

fYear

2014

fDate

21-23 May 2014

Firstpage

435

Lastpage

440

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Supported Cooperative Work in Design (CSCWD), Proceedings of the 2014 IEEE 18th International Conference on

Conference_Location

Hsinchu

Type

conf

DOI

10.1109/CSCWD.2014.6846884

Filename

6846884