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2012 (Vol. 4, Issue: 16)
Article Information:

SVR-D1.2: A Prediction Model for Population Occurrence of Paddy Stem Borer

Lichuan Gu, Jinqin Zhong and Youhua Zhang
Corresponding Author:  Lichuan Gu 

Key words:  Feature selection, kernel alignment, rice paddy stem borer, support vector regression, , ,
Vol. 4 , (16): 2851-2856
Submitted Accepted Published
March 31, 2012 May 12, 2012 August 15, 2012

In this study, we analyse the SVR-based prediction method for selecting the optimal model framework based on kernel matrix. Moreover, SVR-D1.2 is proposed with the help of the kernel matrix’s symmetry and positive definition and kernel alignment. Test results show that there exactly exists the non-line relation between the insect population occurrence and the meteorological factors and the new prediction model, SVR-D1.2, improved prediction accuracy compared with other methods.
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  Cite this Reference:
Lichuan Gu, Jinqin Zhong and Youhua Zhang, 2012. SVR-D1.2: A Prediction Model for Population Occurrence of Paddy Stem Borer.  Research Journal of Applied Sciences, Engineering and Technology, 4(16): 2851-2856.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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