节点文献
基于神经网络的宏观农业生产预测模型的研究
Prediction model of agricultural production based on artificial neural network
【摘要】 为探索宏观农业生产系统预测的新方法 ,构建了基于人工神经网络的预测模型 ,利用 1994— 2 0 0 3年的气象、经济、生产、投入、技术、价格各方面的数据对我国粮食生产进行了拟合分析 ,并预测了 2 0 0 4年粮食总产 ,预测的结果为 4 6 12 5 4 6万t。结果表明 ,与灰色系统相比 ,本文建立的模型具有 90 %以上的拟合精度 ,模型具有容错能力、联想能力和学习能力 ,可以用来尝试解决农业生产系统预测问题。
【Abstract】 To explore new prediction methods of macro agricultural production system, one method of modeling the prediction of agricultural production based on BP (back propagation) model is established. Fitness analysis of foodstuff production was made and the total production of 461.2546 million ton in 2004 was forecasted using all the data of meteorology, economy, production, inputs, technology and prices. Compared with gray system method, the model has over 90% of precise fitness,tolerance on errors, association and studying capacity. This model can be applied to solve issue of prediction of agricultural production system.
【Key words】 artificial neural network; back propagation model; agricultural production system; forecast;
- 【文献出处】 中国农业大学学报 ,Journal of China Agricultural University , 编辑部邮箱 ,2004年05期
- 【分类号】S117
- 【被引频次】9
- 【下载频次】245