In:
Applied Mechanics and Materials, Trans Tech Publications, Ltd., Vol. 644-650 ( 2014-9), p. 2636-2640
Abstract:
Accurate prediction of agricultural prices is beneficial to correctly guide the circulation of agricultural products and agricultural production and realize the equilibrium of supply and demand of agricultural area. On the basis of wavelet neural network, this paper, choosing tomato prices as study object, tomato retail price data from ten collection sites in Hebei province from January, 1st, 2013 to December, 30th, 2013 as samples, builds the tomato price time series prediction model to test price model. As the results show, model prediction error rate is less than 0.01, and the correlation (R2) of predicted value and actual value is 0.908, showing that the model could accurately predict tomatoes price movements. The establishment of the model will provide technical support for tomato market monitoring and early warning and references for related policies.
Type of Medium:
Online Resource
ISSN:
1662-7482
DOI:
10.4028/www.scientific.net/AMM.644-650
DOI:
10.4028/www.scientific.net/AMM.644-650.2636
Language:
Unknown
Publisher:
Trans Tech Publications, Ltd.
Publication Date:
2014
detail.hit.zdb_id:
2251882-4
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