提出了一种新的基于移动检测技术、神经网络和模糊判断方法的城市路网动态交通拥挤预测模型。
A model for urban road network traffic congestion forecast based on probe vehicle technology, fuzzy logic judgement and back-propagation (BP) neural network was proposed.
介绍了用于短期交通流预测的两大类模型：统计预测算法和人工神经网络模型。
A large number of techniques have been applied into short-term traffic flow prediction, which can be classified into two groups: statistical models and artificial neural network model.
针对拉萨市道路交通噪声污染问题，运用人工神经网络理论和方法对拉萨市道路交通噪声的等效连续声级进行预测。
Aiming at the traffic noise problem of Lhasa, the author USES artificial neural network theory and method to predict the equivalent consecutive sound level of traffic noise in Lhasa.
应用推荐