Prediction of Vegetable Price Based on Neural Network and Genetic Algorithm

摘要：

In this paper, the theory and construction methods of four models are presented for predicting the vegetable market price, which are BP neural network model, the neural network model based on genetic algorithm, RBF neural network model and an integrated prediction model based on the three models above. The four models are used to predict the Lentinus edodes price for Beijing Xinfadi wholesale market. A total of 84 records collected between 2003 and 2009 were fed into the four models for training and testing. In summary, the predicting ability of BP neural network model is the worst. The neural network model based on genetic algorithm was generally more accurate than RBF neural network model. The integrated prediction model has the best results.

关键词： genetic algorithm neural network prediction vegetables price

作者: Changshou Luo Qingfeng Wei Liying Zhou Junfeng Zhang Sufen Sun

作者单位: Institute of Information on Science and Technology of Agriculture, Beijing Academy of Agriculture an China Agricultural University Library, Beijing 100094, P.R. China

会议类型: 国际会议

会议名称: The 4th IFIP International on Computer and Computing Technologies in Agriculture and the 4th Symposium on Development of Rural Information(第四届国际计算机及计算机技术在农业中的应用研讨会暨第四届中国农业信息化发展论坛 CCTA 2010)

会议地点: 南昌

会议语种:英文

页码: 672-681

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）