Study of Prognostic Method for Distributive Patterns of Summer Rainfall Based on Fuzzy Support Vector Machine

Author

Desheng Fu ; Liangliang Xu

Author_Institution

Network Monitoring Eng. Center of Jiangsu Province, Nanjing, China

fYear

2012

fDate

2-4 Nov. 2012

Firstpage

509

Lastpage

512

Abstract

Business practices over the years show that three types of rainfall patterns basically reflect the characteristics of summer rainfall in eastern China, and have great practical value for business forecasting. Therefore, in this paper, on the basis of one-versus-one support vector machine multi-classification algorithm, combining with the fuzzy support vector machine, a new model is put forward, and we apply it to the prognosis of summer rainfall pattern. The experiments show that the model has better results than the ordinary one-versus-one SVM multi-classification method and the traditional statistical method on the prognosis experiments of summer rainfall pattern.

Keywords

business data processing; climate mitigation; fuzzy set theory; geophysics computing; monsoons; pattern classification; rain; support vector machines; weather forecasting; East Asian monsoon climate zone; business forecasting; business practices; distributive summer rainfall patterns; eastern China; fuzzy support vector machine; one-versus-one support vector machine multiclassification algorithm; prognostic method; statistical method; summer rainfall pattern forecasting model; summer rainfall pattern prognosis; weather forecasting problems; Accuracy; Forecasting; Kernel; Ocean temperature; Predictive models; Support vector machines; Training; fuzzy support vector machine; multi-class classification; prognostic method; summer rainfall pattern;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Information Networking and Security (MINES), 2012 Fourth International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4673-3093-0

Type

conf

DOI

10.1109/MINES.2012.206

Filename

6405733