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

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 laye...

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Bibliographic Details
Main Authors: Zhe-min LI, Li-guo CUI, Shi-wei XU, Ling-yun WENG, Xiao-xia DONG, Gan-qiong LI, Hai-peng YU
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2013-12-01
Series:Journal of Integrative Agriculture
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Online Access:http://www.sciencedirect.com/science/article/pii/S2095311913606103
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Summary: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.
ISSN:2095-3119