Title :
Climate Prediction by SVM Based on Initial Conditions
Author :
Deji, Wang ; Bo, Xu ; Faquan, Zhang ; Jianting, Li ; Guangcai, Li ; Bingyu, Sun
Author_Institution :
Training Centre of Nat. Tobacco Monopoly Bur., Zhengzhou, China
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.
Keywords :
agriculture; climate mitigation; support vector machines; SVM training; agriculture; climate prediction model; support vector machine; Cities and towns; Fertilizers; Fuzzy systems; Industrial training; Kernel; Monopoly; Pipelines; Sun; Support vector machine classification; Support vector machines; Climate prediction; Initial conditions; SVM;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.566
