Climate prediction by SVM based on initial conditions

Authors:
Wang Deji;Xu Bo;Zhang Faquan;Li Jianting;Li Guangcai;Sun Bingyu
Affiliations:
Training Centre of National Tobacco Monopoly Bureau, Zhengzhou city, China and PetroChina Pipeline Research and Development Center, Langfang city, China;PetroChina Pipeline Research and Development Center, Langfang city, China;Zhengzhou Institute of Light Industry, Zhengzhou, China;PetroChina Pipeline Research and Development Center, Langfang city, China;Training Centre of National Tobacco Monopoly Bureau, Zhengzhou city, China;Training Centre of National Tobacco Monopoly Bureau, Zhengzhou city, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Year:
2009

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Abstract

The climate model is the crucial factor for agriculture. However, the climate variables, which were strongly corrupted by noises or fluctuations, are complicated process and can not be reconstructed by a common method. In the paper, we adapt the SVM to predict it. Specifically, we incorporate the initial condition on climate variables to the training of SVM. The numerical results show the effectiveness and efficiency of the approach.