Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network

文献类型： 外文期刊

第一作者： Li Zhe-min

作者： Li Zhe-min;Cui Li-guo;Xu Shi-wei;Weng Ling-yun;Dong Xiao-xia;Li Gan-qiong;Yu Hai-peng

作者机构：

关键词： chaos theory;chaotic neural network;neural network technology;short-term prediction;weekly retail price of eggs

期刊名称：JOURNAL OF INTEGRATIVE AGRICULTURE （ 影响因子：2.848； 五年影响因子：2.979 ）

ISSN： 2095-3119

年卷期： 2013 年 12 卷 12 期

页码：

收录情况： SCI

摘要： This paper establishes a short-term prediction model of weekly retail prices for eggs based on chaotic neural network with the weekly retail prices of eggs from January 2008 to December 2012 in China. In the process of determining the structure of the chaotic neural network, the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension, and then the number of hidden layer nodes is estimated by trial and error. Finally, this model is applied to predict the retail prices of eggs and compared with ARIMA. The result shows that the chaotic neural network has better nonlinear fitting ability and higher precision in the prediction of weekly retail price of eggs. The empirical result also shows that the chaotic neural network can be widely used in the field of short-term prediction of agricultural prices.

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