Then sensitivity analysis on the factors of temperature and traffic loading is conducted and a short-term rutting prediction model is developed.
分析过程中进行了路面车辙的温度和交通敏感性分析，并进行了针对其短期发生过程的预估模型研究。
Method named BAYESIAN combined neural network model is proposed for short term traffic flow prediction in this paper.
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。
Based on local linear prediction model of chaotic time series, short-term load forecasting method on multi-embedding dimension is presented.
基于混沌时间序列的局域线性预测模型，提出了多嵌入维的短期负荷预测方法。
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