Fangce Guo

703 total citations
31 papers, 520 citations indexed

About

Fangce Guo is a scholar working on Building and Construction, Transportation and Control and Systems Engineering. According to data from OpenAlex, Fangce Guo has authored 31 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Building and Construction, 16 papers in Transportation and 13 papers in Control and Systems Engineering. Recurrent topics in Fangce Guo's work include Traffic Prediction and Management Techniques (21 papers), Transportation Planning and Optimization (14 papers) and Traffic control and management (12 papers). Fangce Guo is often cited by papers focused on Traffic Prediction and Management Techniques (21 papers), Transportation Planning and Optimization (14 papers) and Traffic control and management (12 papers). Fangce Guo collaborates with scholars based in United Kingdom, China and United States. Fangce Guo's co-authors include Rajesh Krishnan, John Polak, Aruna Sivakumar, Junyi Li, Lin Zhu, Tang Li, Goran Štrbac, Simon Hu, Jiangbo Wang and Xiqun Chen and has published in prestigious journals such as Applied Energy, Energy and Buildings and Transportation Research Part C Emerging Technologies.

In The Last Decade

Fangce Guo

30 papers receiving 507 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fangce Guo United Kingdom 14 343 264 214 119 80 31 520
Daniel J. Dailey United States 12 219 0.6× 219 0.8× 232 1.1× 148 1.2× 43 0.5× 44 446
Jordi Casas Spain 10 224 0.7× 312 1.2× 292 1.4× 137 1.2× 21 0.3× 44 486
Sakib Mahmud Khan United States 13 164 0.5× 143 0.5× 129 0.6× 112 0.9× 87 1.1× 42 447
Zhanbo Sun China 11 355 1.0× 328 1.2× 478 2.2× 257 2.2× 75 0.9× 48 672
Minghui Ma China 15 257 0.7× 343 1.3× 423 2.0× 174 1.5× 61 0.8× 54 575
Hoàng Nguyên Australia 8 217 0.6× 146 0.6× 113 0.5× 53 0.4× 23 0.3× 10 375
Yi Hou United States 12 310 0.9× 278 1.1× 332 1.6× 355 3.0× 110 1.4× 42 747
Bernhard Friedrich Germany 12 309 0.9× 332 1.3× 400 1.9× 224 1.9× 81 1.0× 88 650
Romain Billot France 9 165 0.5× 228 0.9× 245 1.1× 140 1.2× 80 1.0× 21 425
Yangxin Lin China 7 161 0.5× 116 0.4× 195 0.9× 144 1.2× 56 0.7× 11 385

Countries citing papers authored by Fangce Guo

Since Specialization
Citations

This map shows the geographic impact of Fangce Guo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fangce Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fangce Guo more than expected).

Fields of papers citing papers by Fangce Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fangce Guo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fangce Guo. The network helps show where Fangce Guo may publish in the future.

Co-authorship network of co-authors of Fangce Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Fangce Guo. A scholar is included among the top collaborators of Fangce Guo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fangce Guo. Fangce Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Guo, Fangce, et al.. (2025). Analysing the impact of electric vehicle charging on households: An interrelated load profile generation approach. Energy and Buildings. 335. 115558–115558. 6 indexed citations
2.
Rago, Antonio, et al.. (2025). Heterogeneous graph neural networks with post-hoc explanations for multi-modal and explainable land use inference. Information Fusion. 120. 103057–103057. 1 indexed citations
3.
Li, Xiaohui, Zhenpo Wang, Lei Zhang, et al.. (2024). Electric vehicle charging flexibility assessment for load shifting based on real-world charging pattern identification. eTransportation. 23. 100367–100367. 5 indexed citations
4.
Guo, Fangce, et al.. (2023). An Online Optimal Bus Signal Priority Strategy to Equalise Headway in Real-Time. Information. 14(2). 101–101. 2 indexed citations
5.
Liu, Kai, et al.. (2023). Modular Bus Unit Scheduling for an Autonomous Transit System under Range and Charging Constraints. Applied Sciences. 13(13). 7661–7661. 14 indexed citations
6.
Guo, Fangce, et al.. (2023). Car-following model calibration with load effect as additional optimisation objective. Structure and Infrastructure Engineering. 21(10). 1623–1640. 2 indexed citations
7.
8.
Guo, Fangce, et al.. (2023). Few-Shot traffic prediction based on transferring prior knowledge from local network. Transportmetrica B Transport Dynamics. 11(1). 5 indexed citations
9.
Li, Junyi, et al.. (2022). Network-scale traffic prediction via knowledge transfer and regional MFD analysis. Transportation Research Part C Emerging Technologies. 141. 103719–103719. 22 indexed citations
10.
Li, Junyi, et al.. (2021). A Domain Adaptation Framework for Short-term Traffic Prediction. 3564–3569. 5 indexed citations
11.
12.
Zhu, Lin, Rajesh Krishnan, Aruna Sivakumar, Fangce Guo, & John Polak. (2019). Traffic Monitoring and Anomaly Detection based on Simulation of Luxembourg Road Network. Spiral (Imperial College London). 382–387. 14 indexed citations
13.
Guo, Fangce, et al.. (2019). Evaluating grid-interactive electric bus operation and demand response with load management tariff. Applied Energy. 255. 113798–113798. 36 indexed citations
14.
Zhu, Lin, Fangce Guo, Rajesh Krishnan, & John Polak. (2018). The Use of Convolutional Neural Networks for Traffic Incident Detection at a Network Level. Transportation Research Board 97th Annual MeetingTransportation Research Board. 13 indexed citations
15.
Zhu, Lin, Fangce Guo, John Polak, & Rajesh Krishnan. (2018). Urban link travel time estimation using traffic states‐based data fusion. IET Intelligent Transport Systems. 12(7). 651–663. 27 indexed citations
16.
Zhu, Lin, Fangce Guo, John Polak, & Rajesh Krishnan. (2017). Multi-Sensor Fusion Based on the Data from Bus GPS, Mobile Phone and Loop Detectors in Travel Time Estimation. Transportation Research Board 96th Annual MeetingTransportation Research Board. 3 indexed citations
17.
Guo, Fangce, Rajesh Krishnan, & John Polak. (2017). The influence of alternative data smoothing prediction techniques on the performance of a two-stage short-term urban travel time prediction framework. Journal of Intelligent Transportation Systems. 21(3). 214–226. 14 indexed citations
18.
Guo, Fangce, Rajesh Krishnan, & John Polak. (2014). Novel Three-Stage Framework for Short-Term Travel Time Prediction Under Normal and Abnormal Traffic Conditions. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 1 indexed citations
19.
Guo, Fangce, Rajesh Krishnan, & John Polak. (2012). Short-Term Traffic Prediction Under Normal and Abnormal Traffic Conditions on Urban Roads. Transportation Research Board 91st Annual MeetingTransportation Research Board. 7 indexed citations
20.
Guo, Fangce, Rajesh Krishnan, & John Polak. (2012). A computationally efficient two-stage method for short-term traffic prediction on urban roads. Transportation Planning and Technology. 36(1). 62–75. 48 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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