DocumentCode :
2398558
Title :
The study of Peony florescence based on improving BP algorithm
Author :
Wang, Ping ; Xu, Haiyang ; Cui, Wenshan
Author_Institution :
Dept. of Sci. & Inf., Qingdao Agric. Univ., Qingdao, China
fYear :
2012
fDate :
19-20 May 2012
Firstpage :
2675
Lastpage :
2678
Abstract :
Heze International Peony Fair develops the local economy, But subject to weather conditions, predicting peony florescence hardly meets the actual date. In order to accurate predicting, multiple linear regression analysis and multiple nonlinear regression analysis have been mentioned. The relationship of the factors which impact the peony florescence such as light, temperature and moisture, etc, is nonlinear, therefore, we adopt the improved BP algorithm and attempts to build prediction models of Peony florescence. Experimental results show that the improved BP algorithm results in Peony than traditional forecasting methods are obviously improved.
Keywords :
agriculture; backpropagation; environmental factors; learning systems; regression analysis; BP algorithm; Heze International Peony Fair; Peony florescence prediction; learning system; local economy; multiple linear regression analysis; multiple nonlinear regression analysis; weather conditions; Algorithm design and analysis; Land surface temperature; Prediction algorithms; Predictive models; Temperature distribution; Training; Forecast model; Improveing BP Algorithm; Peony Florescence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4673-0198-5
Type :
conf
DOI :
10.1109/ICSAI.2012.6223605
Filename :
6223605
Link To Document :
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