In this paper, the use of machine learning algorithms to model Wikipedia traffic using Google's time series dataset is studied. Two data sets were used for time series, data generalization, building a set of machine learning models (XGboost, Logistic Regression, Linear Regression...
5G cellular networks have recently fostered a wide range of emerging applications, but their popularity has led to traffic growth that far outpaces network expansion. This mismatch may decrease network quality and cause severe performance problems. To re
Traffic prediction is the cornerstone of an intelligent transportation system. Accurate traffic forecasting is essential for the applications of smart cities, i.e., intelligent traffic management and urban planning. Although various methods are proposed for spatio-temporal modeling, they ignore the dynamic...
However, the construction of dataset labels often takes a lot of time. Show abstract A hybrid approach of traffic simulation and machine learning techniques for enhancing real-time traffic prediction 2024, Transportation Research Part C: Emerging Technologies Citation Excerpt : In this case, GAT was...
DDoS Attacks: The dataset includes DDoS attacks, which are common in real-world network traffic. The dataset's diversity is enhanced by random content. GET, POST, HEAD, and OPTIONS are the most common HTTP methods. Service-specific Traffic Packets and Datasets: We provide datasets for each ser...
prediction_cutoff The time interval (in minutes) for which the predictive traffic data is processed by the tool. Data providers may supply predictive data for the next 24 hours, week, or other time period. The time-span value for this parameter is used to limit the amount of predictive traf...
To improve the prediction accuracy of traffic flow under the influence of nearby time traffic flow disturbance, a dynamic spatiotemporal graph attention network traffic flow prediction model based on the attention mechanism was proposed. Considering the macroscopic periodic characteristics of traffic flow,...
Traffic Prediction Link Paper & Code & Dataset Collection of Spatial-Temporal Data Mining. Link Relevant Data Repositories Strategic Transport Planning Dataset Link Description: A graph based strategic transport planning dataset, aimed at creating the next generation of deep graph neural networks for...
[Neural Networks] RGDAN: A random graph diffusion attention network for traffic prediction - wengwenchao123/RGDAN
{Sun, Yanfeng and Jiang, Xiangheng and Hu, Yongli and Duan, Fuqing and Guo, Kan and Wang, Boyue and Gao, Junbin and Yin, Baocai},journal={IEEE Transactions on Intelligent Transportation Systems},title={Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction},year={2022}...