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中国农学通报 ›› 2011, Vol. 27 ›› Issue (28): 269-273.

所属专题: 园艺

• 林学 园艺 园林 • 上一篇    下一篇

基于RBF神经网络的蔬菜价格预报研究

孙素芬 罗长寿   

  • 收稿日期:2011-04-26 修回日期:2011-06-28 出版日期:2011-11-05 发布日期:2011-11-05
  • 基金资助:

    基于遗传算法的蔬菜市场价格神经网络预测模型研究

Research on the Prediction of Vegetable Price Based on the RBF Neural Network Model

  • Received:2011-04-26 Revised:2011-06-28 Online:2011-11-05 Published:2011-11-05

摘要:

准确预测农产品市场价格对于农户生产决策与政府调控等具有重要意义。针对蔬菜市场价格预报的复杂性,利用RBF神经网络的特性,应用2003—2007年的香菇市场价格数据建立蔬菜价格预报模型,并对RBF神经网络模型的参数选择进行分析。最后应用模型对2008—2009年的香菇市场价格数据进行预报,通过与BP神经网络模型预报结果进行比较,表明RBF神经网络模型具有更高的预报准确度。

关键词: 厚皮甜瓜, 厚皮甜瓜, SSR, 指纹图谱

Abstract:

Accurate prediction of agricultural product market prices for farmers' production decisions and government regulation is of great significance. Considering the complexity of vegetables price forecast, the prediction model of vegetables price was set up by applying the RBF neural network, using the 2003-2007 mushroom market price data. The model parameters were determined by using simulation experiment, and they were used to predict the 2008-2009 mushroom market prices for Beijing. Its prediction accuracy rating was compared with BP neural network model. The experimental results showed that the RBF neural network model was more accurate than BP neural network model.

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