Overview of traffic incident duration analysis and prediction
Introduction Non-recurrent congestion caused by traffic incident is difficult to predict but
should be dealt with in a timely and effective manner to reduce its influence on road capacity …
should be dealt with in a timely and effective manner to reduce its influence on road capacity …
Dynamic prediction of traffic incident duration on urban expressways: A deep learning approach based on LSTM and MLP
W Zhu, J Wu, T Fu, J Wang, J Zhang… - Journal of intelligent …, 2021 - ieeexplore.ieee.org
Purpose-Efficient traffic incident management is needed to alleviate the negative impact of
traffic incidents. Accurate and reliable estimation of traffic incident duration is of great …
traffic incidents. Accurate and reliable estimation of traffic incident duration is of great …
Real-time traffic accidents post-impact prediction: Based on crowdsourcing data
Traffic accident management is a critical issue for advanced intelligent traffic management.
The increasingly abundant crowdsourcing data and floating car data provide new support for …
The increasingly abundant crowdsourcing data and floating car data provide new support for …
Water quality management using hybrid machine learning and data mining algorithms: An indexing approach
One of the key functions of global water resource management authorities is river water
quality (WQ) assessment. A water quality index (WQI) is developed for water assessments …
quality (WQ) assessment. A water quality index (WQI) is developed for water assessments …
Prediction of the traffic incident duration using statistical and machine-learning methods: A systematic literature review
This paper aims to present a comprehensive review and analysis to demonstrate the main
papers, journals, authors, and trends significantly contributing to the scientific output in …
papers, journals, authors, and trends significantly contributing to the scientific output in …
Improving daily stochastic streamflow prediction: Comparison of novel hybrid data-mining algorithms
In the current paper, the efficiency of three new standalone data-mining algorithms [M5
Prime (M5P), Random Forest (RF), M5Rule (M5R)] and six novel hybrid algorithms of …
Prime (M5P), Random Forest (RF), M5Rule (M5R)] and six novel hybrid algorithms of …
Predicting duration of traffic accidents based on cost-sensitive Bayesian network and weighted K-nearest neighbor
L Kuang, H Yan, Y Zhu, S Tu, X Fan - Journal of Intelligent …, 2019 - Taylor & Francis
With the development of urbanization, road congestion has become increasingly serious,
and an important cause is the traffic accidents. In this article, we aim to predict the duration of …
and an important cause is the traffic accidents. In this article, we aim to predict the duration of …
A deep fusion model based on restricted Boltzmann machines for traffic accident duration prediction
Traffic accidents causing nonrecurrent congestion can decrease the capacity of highways
and increase car emissions. Some models in previous studies have been built based on …
and increase car emissions. Some models in previous studies have been built based on …
Unsupervised anomaly detection based method of risk evaluation for road traffic accident
Elevated road plays a very important role as corridors in urban traffic network, and the
occurrence of traffic accidents often causes a great impact. In that sense, we propose a …
occurrence of traffic accidents often causes a great impact. In that sense, we propose a …
Analysing energy poverty in warm climate zones in Spain through artificial intelligence
D Bienvenido-Huertas, D Sánchez-García… - Journal of Building …, 2023 - Elsevier
Using automated tools to detect energy poverty (EP) is a developing field. Artificial
intelligence and data mining could be used to provide solutions to reduce EP cases. As for …
intelligence and data mining could be used to provide solutions to reduce EP cases. As for …