Lan Shu

1.3k citations
99 papers · 986 · h-index 19

Impact in

Papers in

Lan Shu

90 papers receiving 958 citations

Peers

Lan Shu
Comparison fields: 5 of 91
  • Management Science and Operations Research 322
  • Computational Theory and Mathematics 288
  • Statistics and Probability 78
  • Computer Networks and Communications 207
  • Artificial Intelligence 226
Replace Santanu S. Dey with:
Santanu S. Dey United States
Sergeĭ Ovchinnikov United States
Aditya Mahajan Canada
Stan Zachary United Kingdom
Svetoslav Markov Bulgaria
Ali Muhammad Ali Rushdi Saudi Arabia
Tim van Erven Netherlands
Jordan Stoyanov United Kingdom
Tobias Scheuer Germany
Peter Hellekalek Austria
Lan Shu relative to Santanu S. Dey United States Santanu S. Dey's profile →
Citations per field
00.5×3.5×
Santanu S. Dey · 1×
Citations per year

Countries citing papers authored by Lan Shu

Since Specialization
Citations

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

Fields of papers citing papers by Lan Shu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 99 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201754
2 201143
3 201443
4 201540
5 201640
6 200838
7 202337
8 201835
9 201532
10 202232
11 201531
12 201531
13 201428
14 201424
15 201423
16 202223
17 200821
18 201218
19 201518
20 201816

About Lan Shu

Lan Shu is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications and Control and Systems Engineering, having authored 99 papers that have together received 986 indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (26 papers), Multi-Criteria Decision Making (15 papers), Neural Networks Stability and Synchronization (15 papers), Nonlinear Dynamics and Pattern Formation (8 papers), Distributed Control Multi-Agent Systems (8 papers), Quantum Mechanics and Applications (8 papers), Quantum Computing Algorithms and Architecture (8 papers) and Quantum Information and Cryptography (8 papers). The work is most often cited by research in Management Science and Operations Research (322 citations), Computational Theory and Mathematics (288 citations), Statistics and Probability (78 citations), Computer Networks and Communications (207 citations) and Artificial Intelligence (226 citations). Lan Shu has collaborated with scholars based in China, New Zealand and Russia. Frequent co-authors include Haidong Zhang, Shouming Zhong, Dong Qiu, Xin Wang, Xuehua Li, Zhiwen Mo, Xiu Liu, Jing Jiang, Guimin Huang and Yao Zhang. Their work appears in journals such as Fuzzy Sets and Systems, Soft Computing, International Journal of Fuzzy Systems, Information Sciences and Journal of the Franklin Institute.

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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