Traffic congestion is a significant problem faced by large and growing cities that hurt the
economy, commuters, and the environment. Forecasting the congestion level of a road …

The realization of road traffic prediction not only provides real-time and effective information
for travelers, but also helps them select the optimal route to reduce travel time. Road traffic …

Cities around the world are expanding dramatically, with urban population growth reaching
nearly 2.5 billion people in urban areas and road traffic growth exceeding 1.2 billion cars by …

Resilience is defined as the ability of a system to withstand and recover to a desired level of
performance after the occurrence of a hazard. Community resilience has a significant …

Traffic congestion is a significant problem that adversely affects the economy, environment,
and public health in urban areas worldwide. One promising solution is to forecast road-level …

This study proposes a Naive Bayes (NB) classifier model for predicting congestion and
incident in urban road networks. NB is a machine learning classification model based on …

Load balancing technology can effectively exploit potential enormous compute power
available on distributed systems and achieve scalability. Communication delay overhead on …

Predicting stock market accurately has always fascinated the market analysts. During the
previous few decades assorted machine learning techniques (Regression, RBFN, SOM, BN …

Prediction analysis is a data mining method used to predict future possibilities based on
current information. The traffic prediction techniques have 3 steps which are preprocessing …

道路交通流预测不仅可以为出行者提供实时有效的信息, 而且可以帮助他们选择最佳路径,
减少出行时间, 实现道路交通路径诱导, 缓解交通拥堵. 本文提出了一种基于ARIMA …