Li Pan

4.1k citations
130 papers · 2.6k · 1 hit paper · h-index 27

Impact in

Papers in

Li Pan

121 papers receiving 2.6k citations

Li Pan's Hit Papers

Predicting Short-Term Traffic Flow by Long Short-Term Memory Recurrent Neural Network 2015 · 374 citations
3740+3+7Years since publication100200300

Peers

Li Pan
Comparison fields: 5 of 140
  • Transportation 287
  • Building and Construction 368
  • Artificial Intelligence 854
  • Statistical and Nonlinear Physics 311
  • Computer Vision and Pattern Recognition 401
Replace Jianguo Chen with:
Jianguo Chen China
Weiwei Jiang China
Yong Zhang China
Hao Zhu China
Huayi Wu China
Jun Zhao China
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Ziwei Zhang China
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Li Pan relative to Jianguo Chen China Jianguo Chen's profile →
Citations per field
00.5×3.5×
Jianguo Chen · 1×
Citations per year

Countries citing papers authored by Li Pan

Since Specialization
Citations

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

Fields of papers citing papers by Li Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Li Pan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Li Pan Line = papers co-authored together Li Pan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 130 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Predicting Short-Term Traffic Flow by Long Short-Term Memory Recurrent Neural Network
Hit paper breakdown →
2015374
2 2019233
3 2014220
4 202093
5 200587
6 201780
7 202166
8 201460
9 202260
10 201960
11 201955
12 201953
13 202053
14 201850
15 201547
16 201445
17 202044
18 201743
19 201740
20 201740

About Li Pan

Li Pan is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition, having authored 130 papers that have together received 2.6k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (30 papers), Advanced Graph Neural Networks (15 papers), Opinion Dynamics and Social Influence (15 papers), Topic Modeling (12 papers), Network Security and Intrusion Detection (8 papers), Anomaly Detection Techniques and Applications (6 papers), Access Control and Trust (6 papers) and Traffic Prediction and Management Techniques (6 papers). The work is most often cited by research in Transportation (287 citations), Building and Construction (368 citations), Artificial Intelligence (854 citations), Statistical and Nonlinear Physics (311 citations) and Computer Vision and Pattern Recognition (401 citations). Li Pan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Peng Wu, Yue Wu, Ping Yi, Wenchao Li, Jianhua Li, Qun Niu, Changqing Zou, Ning Liu, Hefeng Wu and Bo Fang. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Computers & Security, Electronics, Neurocomputing and Marine and Petroleum Geology.

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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