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.
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