Predicting Spatiotemporal Traffic Flow Based on Support Vector Regression and Bayesian Classifier-Reference-Cited by-同舟云学术

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Predicting Spatiotemporal Traffic Flow Based on Support Vector Regression and Bayesian Classifier

Published:2015-08 Issue: Volume: Page:
ISSN:
Container-title:2015 IEEE Fifth International Conference on Big Data and Cloud Computing
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Author:

Ahn Jin Young,Ko Eunjeong,Kim EunYi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7307333/7310694/07310727.pdf?arnumber=7310727

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Intelligent Deep Learning Framework for Traffic Flow Imputation and Short-term Prediction Based on Dynamic Features;Knowledge-Based Systems;2024-09

2. Spatiotemporal Data Analysis: A Review of Techniques, Applications, and Emerging Challenges;Springer Optimization and Its Applications;2024

3. Spatio-temporal dynamic change mechanism analysis of traffic conflict risk based on trajectory data;Accident Analysis & Prevention;2023-10

4. PMGCN: Progressive Multi-Graph Convolutional Network for Traffic Forecasting;ISPRS International Journal of Geo-Information;2023-06-16

5. A Deep Review: Techniques, Findings and Limitations of Traffic Flow Prediction Using Machine Learning;Lecture Notes in Mechanical Engineering;2023

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