基于GA-BP神经网络的农业机械化综合水平预测模型

根据1986-2013年我国农业机械化综合水平的统计数据,建立了基于GA-BP神经网络的农业机械化综合水平预测模型。通过对1992-2011年农业机械化综合水平实际值与训练输出值的对比分析,表明该预测模型具有较好的拟合精度;采用该模型对2012年和2013年的农业机械化综合水平进行预测,进一步验证了模型的可靠性。运用该预测模型对2014-2018年的农业机械化综合水平进行预测,结果表明:在2014年我国农业机械化综合水平为61.97%,与我国农业部公布的2014年农业机械化综合水平将超过61%基本相符,2018年我国农业机械化综合水平将达到70%左右。

Predictive Model of Agricultural Mechanization Comprehensive Level Based on the GA-BP Neural Network

According to the statistical data of the comprehensive level of agricultural mechanization in our country in 1986-2013 , predictive model of agricultural mechanization comprehensive level based on the GA -BP neural network was built .Through comparative analysis on real value and training output value of the comprehensive level of agricultural mechanization in 1992-2011 , it shows that the prediction model has good fitting precision .Then use this model to pre-dict the comprehensive level of agricultural mechanization in 2012 and 2013 which further verifies the reliability of the model .And use this predictive model to predict the comprehensive level of agricultural mechanization in 2014-2018 .The results show that the mechanization of agriculture comprehensive level in our country is 61 .97%.This is nearly consistent with the results released by ministry of agriculture that the comprehensive level of agricultural mechanization in 2014 was more than 61%.In 2018 , the comprehensive level of agricultural mechanization will reach 70%more or less .