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Fangce Guo
Fangce Guo
Advanced Research Fellow, Imperial College London
Verified email at imperial.ac.uk - Homepage
Title
Cited by
Cited by
Year
Predictor fusion for short-term traffic forecasting
F Guo, JW Polak, R Krishnan
Transportation research part C: emerging technologies 92, 90-100, 2018
872018
Transferability improvement in short-term traffic prediction using stacked LSTM network
J Li, F Guo, A Sivakumar, Y Dong, R Krishnan
Transportation Research Part C: Emerging Technologies 124, 102977, 2021
782021
Right-of-way reallocation for mixed flow of autonomous vehicles and human driven vehicles
T Li, F Guo, R Krishnan, A Sivakumar, J Polak
Transportation research part C: emerging technologies 115, 102630, 2020
652020
A computationally efficient two-stage method for short-term traffic prediction on urban roads
F Guo, R Krishnan, J Polak
Transportation planning and technology 36 (1), 62-75, 2013
642013
A deep learning approach for traffic incident detection in urban networks
L Zhu, F Guo, R Krishnan, JW Polak
2018 21st international conference on intelligent transportation systems …, 2018
542018
Short-term traffic prediction under normal and incident conditions using singular spectrum analysis and the k-nearest neighbour method
F Guo, R Krishnan, JW Polak
IET Digital Library, 2012
412012
Comparison of modelling approaches for short term traffic prediction under normal and abnormal conditions
F Guo, JW Polak, R Krishnan
13th International IEEE Conference on Intelligent Transportation Systems …, 2010
402010
Evaluating grid-interactive electric bus operation and demand response with load management tariff
Z Wu, F Guo, J Polak, G Strbac
Applied energy 255, 113798, 2019
382019
Urban link travel time estimation using traffic states‐based data fusion
L Zhu, F Guo, JW Polak, R Krishnan
IET Intelligent Transport Systems 12 (7), 651-663, 2018
372018
Short-term traffic prediction under normal and abnormal traffic conditions on urban roads
F Guo, R Krishnan, JW Polak
Transportation Research Board 91st Annual Meeting 12, 1627, 2012
222012
Network-scale traffic prediction via knowledge transfer and regional MFD analysis
J Li, N Xie, K Zhang, F Guo, S Hu, XM Chen
Transportation research part C: emerging technologies 141, 103719, 2022
212022
Traffic monitoring and anomaly detection based on simulation of luxembourg road network
L Zhu, R Krishnan, A Sivakumar, F Guo, JW Polak
2019 IEEE Intelligent Transportation Systems Conference (ITSC), 382-387, 2019
212019
The use of convolutional neural networks for traffic incident detection at a network level
L Zhu, F Guo, R Krishnan, JW Polak
Transportation Research Board 97th Annual MeetingTransportation Research Board, 2018
202018
The influence of alternative data smoothing prediction techniques on the performance of a two-stage short-term urban travel time prediction framework
F Guo, R Krishnan, J Polak
Journal of Intelligent Transportation Systems 21 (3), 214-226, 2017
152017
Early identification of recurrent congestion in heterogeneous urban traffic
L Zhu, R Krishnan, F Guo, JW Polak, A Sivakumar
2019 IEEE Intelligent Transportation Systems Conference (ITSC), 4392-4397, 2019
132019
Short-term traffic prediction under normal and abnormal conditions
F Guo
Imperial College London, 2013
132013
Short-term traffic prediction with deep neural networks and adaptive transfer learning
J Li, F Guo, Y Wang, L Zhang, X Na, S Hu
2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020
112020
A novel three-stage framework for short-term travel time prediction under normal and abnormal traffic conditions
F Guo, R Krishnan, JW Polak
Transportation research board annual meeting, 2014
112014
An analysis of the value of optimal routing and signal timing control strategy with connected autonomous vehicles
T Li, F Guo, R Krishnan, A Sivakumar
Journal of Intelligent Transportation Systems 28 (2), 252-266, 2022
72022
Investigating the transferability of machine learning methods in short-term travel time prediction
J Luan, F Guo, J Polak, N Hoose, R Krishnan
Transportation Research Board 97th Annual MeetingTransportation Research Board, 2018
62018
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