Application of Smooth Support Vector Machine to Predict Precipitation Change in Hanjiang River Basin

CHEN Hua, GUO Jing, XIONG Wei, GUO Sheng-Lian, XU Chong-Yu

Journal of Changjiang River Scientific Research Institute ›› 2008, Vol. 25 ›› Issue (6) : 28-32.

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PDF(1037 KB)
Journal of Changjiang River Scientific Research Institute ›› 2008, Vol. 25 ›› Issue (6) : 28-32.
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Application of Smooth Support Vector Machine to Predict Precipitation Change in Hanjiang River Basin

  •  CHEN   Hua, GUO   Jing, XIONG   Wei, GUO  Sheng-Lian, XU  Chong-Yu
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Abstract

The statistical downscaling method is a hot topic of the downscaling to the GCMs(global climate models). To establish the statistical relationship between the larger scale climate predicted data and observed precipitations in Hanjiang River basin, a statistical downscaling method based on smooth support vector machine(SVM) was discussed and studied. The results showed the SSVM is superior to the traditional multi linear regression method(MLR) and the precision of forecasted precipitations by using SSVM is much higher than the directly output precipitation of the CGCM2. The SSVM is suitable for conducting climate impact studies.

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CHEN Hua, GUO Jing, XIONG Wei, GUO Sheng-Lian, XU Chong-Yu. Application of Smooth Support Vector Machine to Predict Precipitation Change in Hanjiang River Basin[J]. Journal of Changjiang River Scientific Research Institute. 2008, 25(6): 28-32
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