Accurate and timely predicting citywide traffic crowd flows precisely is crucial for public
safety and traffic management in smart cities. Nevertheless, its crucial challenge lies in how …

In this paper, an aggregation approach is proposed for traffic flow prediction that is based on
the moving average (MA), exponential smoothing (ES), autoregressive MA (ARIMA), and …

通过文献梳理, 专家访谈和试验场景构建等方法, 分析了道路指定断面和区域路网宏观交通流
预测的国内外研究现状和发展趋势, 归纳了局部断面交通流预测方法, 包括传统机器学习 …

This paper presents a method of optimizing the elements of a hierarchy of fuzzy-rule-based
systems (FRBSs). It is a hybridization of a genetic algorithm (GA) and the cross-entropy (CE) …

The research status and development trend of macro traffic flow prediction of designated
road sections and regional road network at home and abroad were analyzed by literature …

Accurate short-term traffic flow prediction is essential for real-time traffic control. A linear
hybrid method and a nonlinear hybrid method for short-term traffic flow prediction are …

Smart traffic prediction system provides significant benefits in solving the city traffic
congestion. However, existing smart transportation system needs a lot of real-time traffic …

基于整合移动平均自回归和遗传粒子群优化小波神经网络组合模型的交通流预测Traffic Flow
Predicti Page 1 基于整合移动平均自回归和遗传粒子群优化小波神经 网络组合模型的交通流 …

To predict urban road traffic flow more efficiently and rationally, we established a nonlinear
fractional order grey model that integrates historical trends and residual items and provides …

针对现有预测模型无法在交通大数据中提取交通流序列的内部规律, 且未能充分利用交通流的
时空相关性以实现高精度预测的问题, 提出了一种基于K-最近邻(K-nearest neighbor, KNN) …