结果表明：基于神经网络组合预测模型不仅比单一预测方法能够从整体上提高预测精度，而且能避免最优组合预测模型有时出现负权重的不足。
The result shows that this combined model can improve the precision of forecasting and avoid the shortage of negative weight in the process of optimal mix forecasting model.
并对外汇汇率数据进行了模型构造和预测。 结果表明，组合神经网络在模型的拟合精度和预测准确性方面都有提高。
Through constructing models and making predictions for the currency exchange rate data, we can see that the predictions of combined neural networks are improved.
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.
并且对基于神经网络的组合预测方法进行了研究，提出了一个神经网络和指数平滑模型组合运用的预测算法。
After study of the combined forecasting methods based on the ANN theory, it is put foreword that Exponential-Smooth (ES) and ANN combine a new prediction algorithm.
提出一种新的贝叶斯组合神经网络模型并将其应用于短期交通流量的预测。
Method named BAYESIAN combined neural network model is proposed for short term traffic flow prediction in this paper.
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.
为提高预测精度，解决非线性组合预测中的困难，利用改进BP神经网络对非线性组合预测模型进行了设计。
To improve accuracy of forecast, the paper utilize advanced BP neural network to design for nonlinear combining forecasting model.
文章根据组合预测的理论和BP神经网络对非线性数据良好的逼近特性，提出了基于BP神经网络的灰色预测、多项式回归模型的民用汽车运力组合预测模型。
Based upon the theory of combined forecasting, up-standing identity of BP neural network on approaching non-linear data, put forward a combined forecasting model for civil motors.
为了更好地捕捉天气对负荷的影响，文中提出了一种基于神经网络的趋势组合短期负荷预测思想和模型。
In order to capture the effect of weather on load, this paper presents a novel thought based on ANN and trends combination short term load forecasting.
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.
结果表明，基于神经网络的组合预测模型能有效地提高油气产量预测精度，是比较优越的预测方法。
The results show that this novel method or model as a preferential technique can be used to effectively improve the a…
结果表明，基于神经网络的组合预测模型能有效地提高油气产量预测精度，是比较优越的预测方法。
The results show that this novel method or model as a preferential technique can be used to effectively improve the a…
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