【摘要】 分析了建立卡车路段行程时间预测模型传统方法的不足,考虑到高度非线性的露天矿运输系统有别于公路交通系统,针对卡车运行时间的随机性,采用多因子预测,阐述了应用人工神经网络(ANN)原理和方法对卡车路段行程时间预测的可能性和优越性,建立了预测模型的基本结构,描述了行程时间与其影响因素间的非线性映射关系,从而提出了基于人工神经网络原理的行程时间预测模型。更多还原

【Abstract】 The deficiency of traditional method which is used to build truck link travel time model is analyzed. The theory and method of neural network, and the feasibility and superiority of forecasting the travel time are also discussed. The open mining transportation system of great non-liner relation distinguish from highway traffic system is considered. According to the randomness of truck link travel time, the forecasts of multiple factor is used. The neural network is built, and the non-liner mapping relation between travel time and its influence factors is also described. Thereby the forecasting model of travel time based on neural network is brought forward.更多还原