has been cited by the following article(s):
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[1]
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Comparing idle times of public bicycles in Beijing's free-floating and Seoul's dock-based systems
Cities,
2026
DOI:10.1016/j.cities.2025.106564
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[2]
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Exploring weather-related factors affecting the duration of multiple congestion levels caused by traffic incidents using a multivariate joint frailty survival model
Travel Behaviour and Society,
2026
DOI:10.1016/j.tbs.2025.101209
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[3]
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Proposal of a Machine Learning Approach for Traffic Flow Prediction
Sensors,
2024
DOI:10.3390/s24072348
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[4]
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Investigating Lane Departure Warning Utility with Survival Analysis Considering Driver Characteristics
Applied Sciences,
2024
DOI:10.3390/app14209317
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[5]
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Index for Assessing the Performance Level of Vehicular Traffic on Urban Streets
Urban Science,
2024
DOI:10.3390/urbansci8040204
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[6]
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Optimizing Traffic Flow in Smart Cities: Soft GRU-Based Recurrent Neural Networks for Enhanced Congestion Prediction Using Deep Learning
Sustainability,
2023
DOI:10.3390/su15075949
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[7]
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Proposal of an AI based approach for Urban Traffic Prediction from Mobility Data
2023 IEEE International Conference on Big Data (BigData),
2023
DOI:10.1109/BigData59044.2023.10386509
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[8]
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Design of a Cultural Tourism Passenger Flow Prediction Model in the Yangtze River Delta Based on Regression Analysis
Scientific Programming,
2021
DOI:10.1155/2021/9913468
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[9]
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Short-Term Traffic Flow Prediction Based on Ensemble Machine Learning Strategies
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS),
2021
DOI:10.1109/DDCLS52934.2021.9455594
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