基于此，本文提出了基于集成神经网络的城市道路交通流量的融合预测模型。
Accordingly, this paper proposes a fusion-prediction model of traffic-flow in urban road-intersection based on integrated ANN (Artificial Neural Network).
结果表明，融合预测模型的精度最高，神经网络模型次之，而回归模型精度最低。
The results showed that the prediction precision of the fusion model is the highest, ANN model in the second place, and the regression model in the end.
针对油藏分布预测的问题，提出了一个贝叶斯网络融合模型并设计了相应的算法。
Bayesian fusion model is put foreword with a corresponding algorithm designed to forecast the oil reservoir distribution.
因此本文从分析财务预警问题的特点出发，融合了智能软计算的多种方法建立了完整的预测模型。
After analyzing the characteristic of the early warning problem, we merged many kinds of soft computing methods to construct the prediction model.
应用信息融合技术与不确定性决策理论，构建了对油气储层损害进行识别、诊断、评价和预测的信息融合模型。
An information fusion model for identification, diagnosis, estimation and forecast of formation damage using the data fusion technique and the uncertainty decision theory was established.
利用BP神经网络预测模型融合正交实验法对化学镀工艺进行优化。
The technology optimization of electroless plating can be predicted by BP neural network and orthogonal experiment.
基于灰色理论和自适应数据融合技术的研究，提出一种基于自适应数据融合的新型灰预测GM(1,1)模型，并对整个建模过程进行了理论推导。
A new modeling method of GM (1, 1) was proposed based on the research of grey theory and adaptive data fusion. The whole modeling procedure of this method was established.
由于灰色预测模型对一般的预测模型具有很强的融合力和渗透力，将灰色模型与其它模型结合进行分析和预测，可以提高预测精度。
The grey forecast model has the very strong fusion strength and penetrability to the general model, so it can be combined with other models to improve the forecasting precision.
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.
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.
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