Pingle Yang

754 total citations
34 papers, 516 citations indexed

About

Pingle Yang is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, Pingle Yang has authored 34 papers receiving a total of 516 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Statistical and Nonlinear Physics, 8 papers in Artificial Intelligence and 6 papers in Sociology and Political Science. Recurrent topics in Pingle Yang's work include Complex Network Analysis Techniques (15 papers), Opinion Dynamics and Social Influence (12 papers) and Air Quality and Health Impacts (4 papers). Pingle Yang is often cited by papers focused on Complex Network Analysis Techniques (15 papers), Opinion Dynamics and Social Influence (12 papers) and Air Quality and Health Impacts (4 papers). Pingle Yang collaborates with scholars based in China, Switzerland and France. Pingle Yang's co-authors include Guiqiong Xu, Laijun Zhao, Lixin Zhou, Ying Qian, Zhenyu Zhang, Xin Liu, Haozhen Situ, Qiong Huang, Huiping Chen and Yu Qin and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Pingle Yang

32 papers receiving 496 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Pingle Yang China 14 210 133 90 53 47 34 516
José F. Vicent Spain 15 191 0.9× 110 0.8× 23 0.3× 9 0.2× 21 0.4× 48 534
Menggang Li China 11 157 0.7× 68 0.5× 154 1.7× 46 0.9× 7 0.1× 57 562
Trivik Verma Netherlands 12 159 0.8× 17 0.1× 49 0.5× 24 0.5× 17 0.4× 38 493
Yutao Zhang China 9 150 0.7× 295 2.2× 64 0.7× 36 0.7× 13 0.3× 15 513
Zhi-Dan Zhao China 12 312 1.5× 150 1.1× 37 0.4× 13 0.2× 13 0.3× 27 742
Liping Ni China 8 65 0.3× 80 0.6× 82 0.9× 41 0.8× 46 1.0× 21 359
Douglas W. Mitchell United States 13 54 0.3× 39 0.3× 273 3.0× 31 0.6× 48 1.0× 64 647
Pingfan Xia China 9 67 0.3× 50 0.4× 121 1.3× 23 0.4× 3 0.1× 19 333

Countries citing papers authored by Pingle Yang

Since Specialization
Citations

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

Fields of papers citing papers by Pingle Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pingle Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Pingle Yang. A scholar is included among the top collaborators of Pingle Yang 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 Pingle Yang. Pingle Yang 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
1.
Zhao, Laijun, et al.. (2025). Optimizing logistics hub selection in the integrated network of the China-Europe Railway Express and New International Land-Sea Trade Corridor. Journal of Industrial and Management Optimization. 21(6). 4384–4411. 1 indexed citations
2.
Zhao, Laijun, et al.. (2025). A swarm intelligence-based vaccination strategy for preventing epidemic spreading. Applied Soft Computing. 181. 113413–113413.
3.
Zhao, Laijun, et al.. (2025). Exploring social media users’ disclosures of negative information during the COVID-19 infodemic: the moderating role of personality traits. Online Information Review. 49(4). 848–866. 1 indexed citations
4.
Lü, Zhi, Jian Gao, Jin‐Kao Hao, Pingle Yang, & Lixin Zhou. (2024). Learning driven three-phase search for the maximum independent union of cliques problem. Computers & Operations Research. 164. 106549–106549. 2 indexed citations
5.
Yang, Pingle, et al.. (2023). Disagreement and fragmentation in growing groups. Chaos Solitons & Fractals. 167. 113075–113075. 2 indexed citations
6.
Yang, Pingle, et al.. (2023). A new community-based algorithm based on a “peak-slope-valley” structure for influence maximization on social networks. Chaos Solitons & Fractals. 173. 113720–113720. 8 indexed citations
7.
Yang, Pingle, et al.. (2023). A Two-Stage Hybrid Model for Determining the Scopes and Priorities of Joint Air Pollution Control. Atmosphere. 14(5). 891–891. 1 indexed citations
8.
Zhao, Laijun, et al.. (2022). Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities. Environment Development and Sustainability. 25(7). 7075–7099. 5 indexed citations
9.
Yang, Pingle, et al.. (2022). AIGCrank: A new adaptive algorithm for identifying a set of influential spreaders in complex networks based on gravity centrality. Chinese Physics B. 32(5). 58901–58901. 3 indexed citations
10.
Xu, Guiqiong, et al.. (2022). CPR-TOPSIS: A novel algorithm for finding influential nodes in complex networks based on communication probability and relative entropy. Physica A Statistical Mechanics and its Applications. 603. 127797–127797. 29 indexed citations
11.
Zhao, Laijun, Yi Zhou, Ying Qian, Pingle Yang, & Lixin Zhou. (2022). A novel assessment framework for improving air quality monitoring network layout. Journal of the Air & Waste Management Association. 72(4). 346–360. 4 indexed citations
12.
Xu, Guiqiong, et al.. (2022). TSIFIM: A three-stage iterative framework for influence maximization in complex networks. Expert Systems with Applications. 212. 118702–118702. 32 indexed citations
13.
Xu, Guiqiong, et al.. (2022). A novel potential edge weight method for identifying influential nodes in complex networks based on neighborhood and position. Journal of Computational Science. 60. 101591–101591. 42 indexed citations
14.
Zhao, Laijun, et al.. (2021). How to achieve synergy between carbon dioxide mitigation and air pollution control? Evidence from China. Sustainable Cities and Society. 78. 103609–103609. 98 indexed citations
15.
Xu, Guiqiong, et al.. (2020). TNS-LPA: An Improved Label Propagation Algorithm for Community Detection Based on Two-Level Neighbourhood Similarity. IEEE Access. 9. 23526–23536. 16 indexed citations
16.
Zhou, Ta, et al.. (2019). A Screening Mechanism Fast-Aggregation-Based Takagi-Sugeno-Kang Fuzzy Classification for Epileptic Electroencephalograms Signal. Journal of Medical Imaging and Health Informatics. 9(7). 1458–1463. 1 indexed citations
17.
Zhou, Ta, et al.. (2018). Classification of Epileptic Electroencephalograms Signal Based on Improved Extreme Learning Machine. Journal of Medical Imaging and Health Informatics. 8(1). 33–37. 3 indexed citations
18.
Yang, Pingle, Xin Liu, & Guiqiong Xu. (2018). A dynamic weighted TOPSIS method for identifying influential nodes in complex networks. Modern Physics Letters B. 32(19). 1850216–1850216. 31 indexed citations
19.
Situ, Haozhen, et al.. (2017). Multi-party quantum summation without a trusted third party based on single particles. International Journal of Quantum Information. 15(2). 1750010–1750010. 37 indexed citations
20.
Yang, Pingle. (2010). Design of Uncapacitated Hub-and-Spoke Logistics Networks with Single Allocation. Journal of Transportation Systems Engineering and Information Technology. 2 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by José F. Vicent Breakdown of academic impact, for papers by Menggang Li Breakdown of academic impact, for papers by Trivik Verma Breakdown of academic impact, for papers by Yutao Zhang Breakdown of academic impact, for papers by Zhi-Dan Zhao Breakdown of academic impact, for papers by Liping Ni Breakdown of academic impact, for papers by Douglas W. Mitchell Breakdown of academic impact, for papers by Pingfan Xia
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