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2018
Real-Time Level-of-Service Maps Generation from CCTV Videos

Transportation Research Board 97th Annual Meeting, 11p

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2018
Predicting Incident Duration Using Random Forests

Transportation Research Board 97th Annual Meeting, 8p

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2018
2018
Multiple Spatio-temporal Scales Traffic Forecasting Based on Deep Learning Approach

Transportation Research Board 97th Annual Meeting, 18p

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2018
Forecasting subway demand in large-scale networks: a deep learning approach

Transportation Research Board 97th Annual Meeting, 7p

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2018
Carsharing Trip Characteristic Analysis: Do Users Choose Carsharing Rather Than Taxi to Economize?

Transportation Research Record: Journal of the Transportation Research Board, Volume 2672, Issue 42, pp 115-126

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2018
2018
An Improved Deep Belief Network Model for Road Safety Analyses

Transportation Research Board 97th Annual Meeting, 17p

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2018
Recognizing typical merchant ship categories based on a deep network

Transportation Research Board 97th Annual Meeting, 7p

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2017
Identifying Parameters for Microsimulation Modeling of Traffic in Inclement Weather

Transportation Research Record: Journal of the Transportation Research Board, Issue 2613, pp 52–60

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2017
2017
Multicontextual Machine-Learning Approach to Modeling Traffic Impact of Urban Highway Work Zones

Transportation Research Record: Journal of the Transportation Research Board, Issue 2645, pp 184–194

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2017
2017
A New Analytic Neuro-Fuzzy Model For Work Zone Capacity Estimation

Transportation Research Board 96th Annual Meeting, 16p

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2017
Detecting Imminent Lane Change Maneuvers in Connected Vehicle Environments

Transportation Research Record: Journal of the Transportation Research Board, Issue 2645, pp 168–175

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2017
Real-Time Associative Memory–Based Rear-End Collision Warning System

Transportation Research Record: Journal of the Transportation Research Board, Issue 2621, pp 1–9

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2017
2017
A Model Based on Deep Learning for Predicting Travel Mode Choice

Transportation Research Board 96th Annual Meeting, 17p

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2017
Estimation of Clay Compaction Parameters by Machine Learning Techniques

Transportation Research Board 96th Annual Meeting, 13p

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