Visualization model of big data based on self-organizing feature map neural network and graphic theory for smart cities
Sign Up to like & getrecommendations! Published in 2018 at "Cluster Computing"
DOI: 10.1007/s10586-018-1848-1
Abstract: The process of current urban and accelerating the number of motor vehicles increased rapidly resulting in road traffic pressure is increasing, we need to analyze large data traffic in the city, to guide urban road… read more here.
Keywords: traffic; based self; visualization model; self organizing ... See more keywords
Visual analysis of traffic data based on topic modeling (ChinaVis 2017)
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Visualization"
DOI: 10.1007/s12650-018-0481-7
Abstract: The spatio-temporal urban movement patterns can be extracted from the massive trajectory data recorded by GPS devices. Effectively analyzing the massive and complex traffic data and then finding useful information hidden in such data constitute… read more here.
Keywords: traffic; visual analysis; traffic data; semantics ... See more keywords
Traffic inputs for pavement ME design using Oklahoma data
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Pavement Research and Technology"
DOI: 10.1007/s42947-019-0020-5
Abstract: Mechanistic-empirical pavement design guide (MEPDG) or Pavement ME Design requires traffic inputs in three levels based on the availability of data and the importance of the project. The availability of site-specific (Level 1) traffic data… read more here.
Keywords: traffic; traffic inputs; traffic data; pavement design ... See more keywords
Non-recurrent Traffic Congestion Detection with a Coupled Scalable Bayesian Robust Tensor Factorization Model
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.10.091
Abstract: Non-recurrent traffic congestion (NRTC) usually brings unexpected delays to commuters. Hence, it is critical to accurately detect and recognize the NRTC in a real-time manner. The advancement of road traffic detectors and loop detectors provides… read more here.
Keywords: traffic; framework; tensor; bayesian robust ... See more keywords
Harmonized Annual Averaged Traffic Data at Street Segment Level for European Cities
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Data"
DOI: 10.1038/s41597-025-05698-y
Abstract: Traffic flow data in Europe are collected locally by city authorities using different systems and standards, making it difficult to compare cities or evaluate large-scale maps, such as those used for emission inventories. To address… read more here.
Keywords: european cities; traffic data; averaged traffic; harmonized annual ... See more keywords
Innovative method for traffic data imputation based on convolutional neural network
Sign Up to like & getrecommendations! Published in 2018 at "IET Intelligent Transport Systems"
DOI: 10.1049/iet-its.2018.5114
Abstract: The quality of traffic data is crucial for modern transportation planning and operations. However, data could be missing for various reasons. Hence, the data imputation approaches which aim at predicting/replacing the missing data or bad… read more here.
Keywords: traffic data; data imputation; method; convolutional neural ... See more keywords
STCDM: Spatio‐Temporal Conditional Diffusion Model for Traffic Data Filling
Sign Up to like & getrecommendations! Published in 2025 at "IET Intelligent Transport Systems"
DOI: 10.1049/itr2.70016
Abstract: While the utilization of transportation systems is on the rise, significant data quality concerns persist, including data loss and noise arising from network transmission delays and detector malfunctions. Various methods for data imputation exist, among… read more here.
Keywords: diffusion model; traffic data; diffusion; spatio temporal ... See more keywords
Adaptive learning on mobile network traffic data
Sign Up to like & getrecommendations! Published in 2019 at "Connection Science"
DOI: 10.1080/09540091.2018.1512557
Abstract: ABSTRACT Machine learning based mobile traffic classification has become a popular topic in recent years. As mobile traffic data is dynamic in nature, the static model has become ineffective for the task of classifying future… read more here.
Keywords: concept drift; traffic; classification; model ... See more keywords
The effect of traffic data source on deterioration rates of heavy-duty flexible pavements
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Pavement Engineering"
DOI: 10.1080/10298436.2016.1240562
Abstract: Abstract The purpose of this study is to assess the effect of traffic data source (estimated vs. actual) on predicted progression rates of roughness and rutting for heavy-duty flexible pavements of rural freeways. Progression rates… read more here.
Keywords: traffic; deterioration; data source; heavy duty ... See more keywords
Spatio-temporal graph neural networks for missing data completion in traffic prediction
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Geographical Information Science"
DOI: 10.1080/13658816.2024.2381221
Abstract: Abstract Missing traffic data completion is a key part of the construction of a smart city. However, due to cost constraints and other reasons, many locations do not have sensors to record traffic data. Most… read more here.
Keywords: data completion; traffic data; missing data; spatio temporal ... See more keywords
Nonlinear Traffic Data Reconstruction in large-scale Internet of Vehicle Systems: A neural network approach
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3160464
Abstract: Multi-Access Edge Computing (MEC) can reduce transmission costs and provide faster interactive responses in cloud server-centric Internet of Vehicle (IoV) scenarios. However, the resource space of MEC server is limited, and the large amount of… read more here.
Keywords: neural network; internet vehicle; traffic; reconstruction ... See more keywords