Guangyuan Pan

543 citations
42 papers · 324 indexed · h-index 12
Topics
Traffic Prediction and Management Techniques (11 papers)Infrastructure Maintenance and Monitoring (9 papers)Smart Materials for Construction (7 papers)
Partner nations
ChinaCanadaHong Kong

In The Last Decade

Guangyuan Pan

33 papers receiving 318 citations

Peers

Guangyuan Pan
Comparison fields: 5 of 63
  • Electrical and Electronic Engineering 82
  • Civil and Structural Engineering 58
  • Building and Construction 55
  • Artificial Intelligence 50
  • Control and Systems Engineering 47
Replace Allou Samé with:
Allou Samé France
Matti Kutila Finland
Tahar Ezzedine Tunisia
Ryszard Sroka Poland
Tadeusz Żegleń Poland
Norman C. F. Tse Hong Kong
Majura F. Selekwa United States
Mao Yang China
Rui Yan China
Guangyuan Pan relative to Allou Samé France Allou Samé's profile →
Citations per field
00.5×1.5×1.9×
Allou Samé · 1×
Citations per year

Countries citing papers authored by Guangyuan Pan

Since Specialization
Citations

This map shows the geographic impact of Guangyuan Pan'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 Guangyuan Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangyuan Pan more than expected).

Fields of papers citing papers by Guangyuan Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guangyuan Pan. 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 Guangyuan Pan. The network helps show where Guangyuan Pan may publish in the future.

Co-authorship network of co-authors of Guangyuan Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Guangyuan Pan. A scholar is included among the top collaborators of Guangyuan Pan 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 Guangyuan Pan. Guangyuan Pan 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
#WorkIndexed citations
1 6
2 0
3 0
4 0
5 1
6 0
7 0
8 5
9 22
10 1
11 24
12 9
13 7
14 5
15 23
16 6
17 33
18
Adaptive Traffic Signal Control with Deep Reinforcement Learning: An Exploratory Investigation
2
19 12
20 3

About Guangyuan Pan

Guangyuan Pan is a scholar working on Building and Construction, Pollution and Civil and Structural Engineering, having authored 42 papers that have together received 324 indexed citations. Recurring topics across this work include Traffic Prediction and Management Techniques (11 papers), Infrastructure Maintenance and Monitoring (9 papers) and Smart Materials for Construction (7 papers). The work is most often cited by research in Building and Construction (55 citations), Safety, Risk, Reliability and Quality (35 citations) and Civil and Structural Engineering (58 citations). Guangyuan Pan has collaborated with scholars based in China, Canada and Hong Kong. Frequent co-authors include Liping Fu, Ming Yu, Qili Chen, Yang Wu, Wenbai Chen, Hongsheng Li, Junfei Qiao, Di Lu, Liping Fu and Honggui Han. Their work appears in journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Microwave Theory and Techniques.

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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