Pei-Ling Zhou

474 citations
38 papers · 359 · h-index 11

Impact in

Papers in

Pei-Ling Zhou

35 papers receiving 351 citations

Peers

Pei-Ling Zhou
Comparison fields: 5 of 77
  • Statistical and Nonlinear Physics 167
  • Economics and Econometrics 152
  • Cognitive Neuroscience 69
  • Signal Processing 30
  • Finance 25
Replace Juan I. Perotti with:
Juan I. Perotti Argentina
F. Pozzi Australia
Radu Manuca United States
Amir H. Darooneh Iran
Yonghong Chen China
Fail Gafarov Russia
Tatyana S. Turova Sweden
Ana V. Coronado Spain
Carlos Ibarra-Valdez Mexico
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Citations per field
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Citations per year

Countries citing papers authored by Pei-Ling Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Pei-Ling Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pei-Ling Zhou. 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 Pei-Ling Zhou. The network helps show where Pei-Ling Zhou may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201244
2 200528
3 200627
4 200926
5 198925
6 201024
7 200715
8 200715
9 200813
10 200413
11 200612
12 200510
13 200610
14 200510
15 200510
16 20129
17 20128
18 19978
19 20227
20 20076

About Pei-Ling Zhou

Pei-Ling Zhou is a scholar working on Economics and Econometrics, Statistical and Nonlinear Physics, Computer Networks and Communications, Cognitive Neuroscience and Condensed Matter Physics, having authored 38 papers that have together received 359 indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (19 papers), Complex Network Analysis Techniques (11 papers), Chaos control and synchronization (6 papers), Opinion Dynamics and Social Influence (6 papers), Theoretical and Computational Physics (4 papers), Financial Risk and Volatility Modeling (3 papers), Nonlinear Dynamics and Pattern Formation (3 papers) and Neural dynamics and brain function (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (167 citations), Economics and Econometrics (152 citations), Cognitive Neuroscience (69 citations), Signal Processing (30 citations) and Finance (25 citations). Pei-Ling Zhou has collaborated with scholars based in China, Switzerland and Hong Kong. Frequent co-authors include Tao Zhou, Shi‐Min Cai, Bing-Hong Wang, Bruce C. Gates, Huijie Yang, Yanbo Zhou, Zhongqian Fu, Qiang Liu, Guang Zhao and Hong‐Jin Sun. Their work appears in journals such as Chinese Physics Letters, Physica A Statistical Mechanics and its Applications, Journal of Vision, Frontiers in Public Health and Early Childhood Education Journal.

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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