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.
对时间序列的一类预测模型进行了研究，把灰色模型与BP神经网络模型组合建模，通过实例分析取得好的效果。
In this paper, by using the gray system theory and the dynamic BP neural network, the combination forecasting model are discussed.
提出了设备运行状态综合预测模型，神经网络和灰色理论的组合应用，提高了状态预测的准确性。
A synthetic condition prediction model is presented, using neural network and grey theory together make it possible to predict accurately.
应用推荐