Lan Yang

481 citations
20 papers · 340 · h-index 9

Impact in

Papers in

Lan Yang

17 papers receiving 337 citations

Peers

Lan Yang
Comparison fields: 5 of 70
  • Statistical and Nonlinear Physics 190
  • Computer Networks and Communications 70
  • Communication 16
  • Management Science and Operations Research 24
  • Sociology and Political Science 84
Replace Eleni Stai with:
Eleni Stai Greece
Federico Corò Italy
Mark Liptrott United Kingdom
Ye Deng China
Christian Quadri Italy
Hadi Tabatabaee Malazi Iran
Aniello De Santo United States
Jae C. Oh United States
Enyan Dai United States
S. Karthika India
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Citations per field
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Citations per year

Countries citing papers authored by Lan Yang

Since Specialization
Citations

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

Fields of papers citing papers by Lan Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lan Yang, 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 Lan Yang Line = papers co-authored together Lan Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2019147
2 202035
3 201926
4
Network Anomaly Detection Using One Class Support Vector Machine
200823
5 201822
6 202320
7 202315
8 201914
9 201713
10 20236
11 20246
12 20214
13 20243
14 20203
15 20181
16 20171
17 20221
18 20250
19 20240
20 20210

About Lan Yang

Lan Yang is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Management Science and Operations Research, Biomedical Engineering and Computer Networks and Communications, having authored 20 papers that have together received 340 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (8 papers), Opinion Dynamics and Social Influence (7 papers), Game Theory and Applications (5 papers), Non-Invasive Vital Sign Monitoring (3 papers), Network Security and Intrusion Detection (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Cardiovascular and exercise physiology (2 papers) and Heart Rate Variability and Autonomic Control (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (190 citations), Computer Networks and Communications (70 citations), Communication (16 citations), Management Science and Operations Research (24 citations) and Sociology and Political Science (84 citations). Lan Yang has collaborated with scholars based in China, Macao and Italy. Frequent co-authors include Zhiwu Li, Alessandro Giua, Naiqi Wu, Junqi Guo, Zhenhua Yu, Ahmed M. El‐Sherbeeny, Mohammed A. El-Meligy, Shaoyan Zhang, Rui Zhang and Jianmin Jiang. Their work appears in journals such as IEEE Transactions on Fuzzy Systems, IEEE Access, Expert Systems with Applications, Sensors and IEEE Transactions on Systems Man and Cybernetics Systems.

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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