对比发现，利用组合灰色神经网络模型预测的位移值较单独的灰色模型预测的位移值具有更高的精度。
It is more accurate of the forecasting results by the composite gray neural network model than that by the only gray models by comparison.
针对城市电力系统年用电量增长的特点，将灰色神经网络模型GNNM(1,1)引入城市年用电量预测。
According to the speciality of electricity demand development in a city, the grey neural network model GNNM (1, 1) was introduced into the field of city electricity demand forecasting in this paper.
故将灰色系统和神经网络有机融合，形成灰色神经网络模型，能弥补单一使用这两种模型时的不足，达到优良的数据处理和预测效果。
Therefore, combining grey system with neural network, the grey neural network can make up the shortage of using single model to achieving excellent data processing and predictive validity.
应用推荐