用灰色神经网络组合模型预测农机总动力发展

农机总动力的需求预测是一个复杂的非线形系统，其发展变化具有增长性和波动性。该文首先在灰色预测模型的基础上建立了新陈代谢型灰色预测模型群，然后结合灰色GM(1,1)模型和BP网络模型的优缺点，建立了串联新陈代谢型灰色神经网络组合预测模型，并对中国农机总动力需求进行了预测，结果表明预测值和实际结果有很好的一致性。

Method for estimating total power of agricultural machinery based on mixed grey neural network

The demand for total power of agricultural machinery is a complicated non-linear system, whose developmental changes have dual trends of increase and fluctuation. This paper established metabolic GM(1,1) models based on grey prediction model firstly. The authors also analyzed the merits as well as defects of BP neural network and grey prediction method, then combined the two methods to establish a combined metabolic estimation model named serial grey neural network, and estimated the total power demand of agricultural machinery of China. Case study validated the effectiveness of the proposed model.