DocumentCode
507301
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
Volume
5
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
578
Lastpage
581
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.566
Filename
5360557
Link To Document