DocumentCode
2795432
Title
Climate model by SVM based on experienced knowledge in tobacco region division
Author
Deji, Wang ; Bo, Xu ; Guangcai, Li ; Guoqun, Chen ; Bingyu, Sui
Author_Institution
Training Centre of Nat. Tobacco Monopoly Bur., Zhengzhou, China
fYear
2009
fDate
17-19 June 2009
Firstpage
3281
Lastpage
3284
Abstract
Tobacco region division is vital to improve the quality of the tobacco. And the climate model is the most important factor for the division. However, the climate variable, which was strongly corrupted by noises or fluctuations, can not be reconstructed by common method. In order to improve the performance of regression, the experienced knowledge about climate variable is incorporated in the training of SVM. The experimental results demonstrate the effectiveness and efficiency of our approach.
Keywords
support vector machines; tobacco industry; climate model; experienced knowledge based SVM; experienced knowledge based support vector machines; tobacco region division; Biological system modeling; Cities and towns; Kernel; Meteorology; Monopoly; Neural networks; Pipelines; Research and development; Support vector machine classification; Support vector machines; Climate Model; Experienced Knowledge; SVM; Tobacco Region Division;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location
Guilin
Print_ISBN
978-1-4244-2722-2
Electronic_ISBN
978-1-4244-2723-9
Type
conf
DOI
10.1109/CCDC.2009.5192581
Filename
5192581
Link To Document