文献类型： 会议论文
第一作者： YE Lu
作者： YE Lu 1 ; LI Yuping 1 ; LIANG Weihong 1 ; LIU Yanqun 1 ; SONG Qidao 1 ; QIN Xiaoli 1 ;
作者机构： 1.Institute of Scientific and Technical Information, CATAS/Key Lab of Tropical Crops Information Technology Application Research of Hainan Province, Danzhou 571737, China
关键词： PSO;BP Neural Network;Vegetable Price;Prediction
会议名称： International Conference on Intelligent Computation Technology and Automation
主办单位：
页码： 1093-1096
摘要： In order to predict vegetable price accurately, 117 sets of green pepper and related factors price data from 2012 to 2015 in Danzhou city were selected as the sample data, of which 100 groups were training data and 17 groups were test data. Based on analyzing fluctuant features of vegetable price, with the global stochastic optimization idea to optimize initial weights and thresholds of back propagation (BP) neural network, the PSO-BP prediction model concerning vegetable retail price was set up by using the particle swarm optimization (PSO) algorithm. The experimental results indicated that compared with the traditional BP method, the PSO-BP method could overcome the over-fitting problem and the local minima problem, effectively reduced training error and increased the predicting precision.
分类号： tp18-532
- 相关文献
[1]Vegetable Price Prediction Based on PSO-BP Neural Network. Ye Lu,Li Yuping,Liang Weihong,Song Qidao,Liu Yanqun,Qin Xiaoli. 2015
[2]Research on the Optimal Combination Forecasting Model for Vegetable Price in Hainan. YE Lu,LI Yuping,LIU Yanqun,QIN Xiaoli,LIANG Weihong. 2013
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