Dongshu Wang
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- stochastic dynamics and bifurcation 10
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- Neural Networks Stability and Synchronization 16
- Nonlinear Dynamics and Pattern Formation 9
- Modeling and Simulation top 10%
- Fractional Differential Equations Solutions 3
- Applied Mathematics top 10%
- Nonlinear Differential Equations Analysis 9
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- Mathematical and Theoretical Epidemiology and Ecology Models 13
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- Advanced Differential Equations and Dynamical Systems 6
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- Differential Equations and Numerical Methods 3
- Co-authors
- Lihong HuangLongkun TangZuowei CaiXiaoqin ZengLingling ZhangAhmed A. IssaMaximilian AmslerVinay I. Hegde
- Cited by
- Statistical and Nonlinear PhysicsComputer Networks and CommunicationsModeling and Simulation
- Journals
- Acta Materialia (1 paper)IEEE Transactions on Neural Networks and Learning Systems (2 papers)Neurocomputing (3 papers)
- Partner nations
- ChinaSouth KoreaUnited States
In The Last Decade
Dongshu Wang
33 papers receiving 499 citations
Peers
Comparison fields: 5 of 43
- Statistical and Nonlinear Physics 218
- Computer Networks and Communications 351
- Modeling and Simulation 32
- Biomaterials 43
- Applied Mathematics 33
Countries citing papers authored by Dongshu Wang
This map shows the geographic impact of Dongshu Wang'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 Dongshu Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dongshu Wang more than expected).
Fields of papers citing papers by Dongshu Wang
This network shows the impact of papers produced by Dongshu Wang. 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 Dongshu Wang. The network helps show where Dongshu Wang may publish in the future.
Co-authorship network
The 17 scholars most cited alongside Dongshu Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 6 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 10 | |
| 4 | 2023 | 7 | |
| 5 | 2023 | 0 | |
| 6 | 2023 | 22 | |
| 7 | 2022 | 3 | |
| 8 | 2018 | 47 | |
| 9 | 2018 | 34 | |
| 10 | 2018 | 20 | |
| 11 | 2018 | 2 | |
| 12 | 2015 | 13 | |
| 13 | 2015 | 54 | |
| 14 | 2015 | 22 | |
| 15 | 2014 | 21 | |
| 16 | 2013 | 39 | |
| 17 | 2013 | 1 | |
| 18 | 2013 | 8 | |
| 19 | 2013 | 5 | |
| 20 | 2012 | 2 |
About Dongshu Wang
Dongshu Wang is a scholar working on Modeling and Simulation, Applied Mathematics and Statistical and Nonlinear Physics, having authored 35 papers that have together received 502 indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (16 papers), Mathematical and Theoretical Epidemiology and Ecology Models (13 papers), stochastic dynamics and bifurcation (10 papers), Nonlinear Differential Equations Analysis (9 papers), Nonlinear Dynamics and Pattern Formation (9 papers), Advanced Differential Equations and Dynamical Systems (6 papers), Fractional Differential Equations Solutions (3 papers) and Differential Equations and Numerical Methods (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (218 citations), Computer Networks and Communications (351 citations) and Modeling and Simulation (32 citations). Dongshu Wang has collaborated with scholars based in China, South Korea and United States. Frequent co-authors include Lihong Huang, Longkun Tang, Zuowei Cai, Lihong Huang, Xiaoqin Zeng, Lingling Zhang, Ahmed A. Issa, Maximilian Amsler, Vinay I. Hegde and Bi‐Cheng Zhou. Their work appears in journals such as Acta Materialia, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.
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.