Smart City Gnosys

Smart city article details

Title	A Traffic Prediction Model Based On Multi Stream Feature Fusion
ID_Doc	5616
Authors	Musike M.R.; Tiwari R.; Shrivastava R.
Year	2024
Published	Lecture Notes in Electrical Engineering, 1096
DOI	http://dx.doi.org/10.1007/978-981-99-7137-4_16
Abstract	Traffic is constantly changing, traffic supposition is extremely crucial in urban planning congestion control as well as management systems. Long-term traffic predictions help with relevant factors and smart city current traffic reduction. Traffic flow is an important topic because it transports regional factors and patterns regional spatial structure. Traffic prediction is gaining popularity due to its widespread real-world applications in traffic management, urban computing, public safety, and other fields. For intelligent transportation systems, timely and accurate traffic flow prediction is critical. A MSFF-Multi-Stream-Feature-Fusion method is proposed in this paper to remove and incorporate rich features after traffic data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Author Keywords	Data; Feature fusion; Prediction; Tasks; Traffic

Similar Articles

Id	Similarity	Authors	Title	Published
2853	0.893	Li X.; Nie D.	A Multi-Source Data Fusion Model For Traffic Flow Prediction In Smart Cities	Applied Mathematics and Nonlinear Sciences, 9, 1 (2024)
58652	0.88	Swathi V.; Yerraboina S.; Mallikarjun G.; Jhansirani M.	Traffic Prediction For Intelligent Transportation System Using Machine Learning	2022 2nd International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2022 (2022)
38283	0.88	Dhanasekaran S.; Gopal D.; Logeshwaran J.; Ramya N.; Salau A.O.	Multi-Model Traffic Forecasting In Smart Cities Using Graph Neural Networks And Transformer-Based Multi-Source Visual Fusion For Intelligent Transportation Management	International Journal of Intelligent Transportation Systems Research, 22, 3 (2024)
1395	0.876	Tripathi A.N.; Sharma B.	A Deep Review: Techniques, Findings And Limitations Of Traffic Flow Prediction Using Machine Learning	Lecture Notes in Mechanical Engineering (2023)
27462	0.873	Ait Ouallane A.; Bakali A.; Bahnasse A.; Broumi S.; Talea M.	Fusion Of Engineering Insights And Emerging Trends: Intelligent Urban Traffic Management System	Information Fusion, 88 (2022)
22428	0.872	Sreelekha M.; Janarthanan M.	Efficient Traffic Routing With Temporal Fusion Transformers: Addressing Urban Congestion Challenges	SSRG International Journal of Electronics and Communication Engineering, 11, 11 (2024)
934	0.872	Bakir D.; Moussaid K.; Chiba Z.; Abghour N.	A Comprehensive Review Of Traffic Congestion Prediction Models: Machine Learning And Statistical Approaches	2024 IEEE International Conference on Computing, ICOCO 2024 (2024)
53044	0.871	Meng X.; Xie W.; Cui J.	Stmgfn: Spatio-Temporal Multi-Graph Fusion Network For Traffic Flow Prediction	Lecture Notes in Computer Science, 15291 LNCS (2025)
42773	0.87	Zhu W.; Kong H.; Cai W.; Zhu W.	Predicting Urban Traffic Flow Based On Deep Meta-Learning	ACM International Conference Proceeding Series (2024)
8060	0.866	Shouaib M.; Metwally K.; Badran K.	An Enhanced Time-Dependent Traffic Flow Prediction In Smart Cities	Advances in Electrical and Computer Engineering, 23, 3 (2023)