﻿ 基于LS-SVM的改进统计降尺度方法

# 基于LS-SVM的改进统计降尺度方法A Statistical Downscaling Method Based on Least Squares Support Vector Machines

The statistical downscaling method has been more and more utilized in the climate change study for its simplicity and flexibility. A statistical downscaling method based on LS-SVM (least squares support vector machines) was developed and compared with SDSM (Statistical Downscaling Model) to test its ability in downscaling precipitation and temperature in Xiangjiang Basin. The results showed that the method based on LS-SVM has the similar performance with the SDSM method in simulating precipitation, while it was superior to SDSM in simulating temperature. The proposed method still needs to be applied to more regions to make it more suitable for studying the impact on water resources under climate change.

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