Zhenbo Wu

506 total citations
19 papers, 382 citations indexed

About

Zhenbo Wu is a scholar working on Geophysics, Electrical and Electronic Engineering and Control and Systems Engineering. According to data from OpenAlex, Zhenbo Wu has authored 19 papers receiving a total of 382 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Geophysics, 4 papers in Electrical and Electronic Engineering and 3 papers in Control and Systems Engineering. Recurrent topics in Zhenbo Wu's work include earthquake and tectonic studies (11 papers), High-pressure geophysics and materials (9 papers) and Geological and Geochemical Analysis (8 papers). Zhenbo Wu is often cited by papers focused on earthquake and tectonic studies (11 papers), High-pressure geophysics and materials (9 papers) and Geological and Geochemical Analysis (8 papers). Zhenbo Wu collaborates with scholars based in China, Spain and United States. Zhenbo Wu's co-authors include Tao Xu, Jiwen Teng, Xiaobo Tian, Zhongjie Zhang, Chenglong Wu, Zhiming Bai, Yanghua Wang, G. A. Houseman, Yun Chen and Xiaohui Yuan and has published in prestigious journals such as Earth and Planetary Science Letters, Energy Conversion and Management and Energy.

In The Last Decade

Zhenbo Wu

18 papers receiving 357 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhenbo Wu China	12	261	52	37	23	15	19	382
Mathieu Le Breton France	8	162 0.6×	37 0.7×	22 0.6×	18 0.8×	5 0.3×	15	282
Can Ge China	12	277 1.1×	24 0.5×	180 4.9×	6 0.3×	6 0.4×	31	453
Wenfei Mao China	12	229 0.9×	21 0.4×	127 3.4×	12 0.5×	5 0.3×	45	352
Shaobo Yang China	11	47 0.2×	96 1.8×	53 1.4×	60 2.6×	8 0.5×	38	348
Tao Ren China	12	399 1.5×	7 0.1×	235 6.4×	18 0.8×	7 0.5×	54	516
Dimitrios Raptakis Greece	19	873 3.3×	19 0.4×	42 1.1×	9 0.4×	4 0.3×	37	1.2k
Akira Jomori Japan	7	341 1.3×	23 0.4×	22 0.6×	9 0.4×	2 0.1×	14	355
Hiroyuki Goto Japan	12	247 0.9×	12 0.2×	53 1.4×	7 0.3×	6 0.4×	64	368
Yuejun Li China	12	185 0.7×	6 0.1×	82 2.2×	5 0.2×	2 0.1×	33	332
Silvia Bersan Italy	8	130 0.5×	141 2.7×	9 0.2×	5 0.2×	12 0.8×	14	361

Countries citing papers authored by Zhenbo Wu

Since Specialization

Citations

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

Fields of papers citing papers by Zhenbo Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenbo Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenbo Wu. A scholar is included among the top collaborators of Zhenbo Wu 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 Zhenbo Wu. Zhenbo Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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19 of 19 papers shown

Yang, Wei, et al.. (2024). Utilizing machine learning techniques to identify severe sleep disturbances in Chinese adolescents: an analysis of lifestyle, physical activity, and psychological factors. Frontiers in Psychiatry. 15. 1447281–1447281.

Meng, Anbo, Zhenbo Wu, Zhan Zhang, et al.. (2024). Optimal scheduling of integrated energy system using decoupled distributed CSO with opposition-based learning and neighborhood re-dispatch strategy. Renewable Energy. 224. 120102–120102. 3 indexed citations

Meng, Anbo, Hao Yin, Jianqiang Luo, et al.. (2023). A novel network training approach for solving sample imbalance problem in wind power prediction. Energy Conversion and Management. 283. 116935–116935. 19 indexed citations

Meng, Anbo, Zhifeng Xie, Jianqiang Luo, et al.. (2023). An adaptive variational mode decomposition for wind power prediction using convolutional block attention deep learning network. Energy. 282. 128945–128945. 16 indexed citations

Meng, Anbo, Hai‐Tao Zhang, Hao Yin, et al.. (2023). A novel multi-gradient evolutionary deep learning approach for few-shot wind power prediction using time-series GAN. Energy. 283. 129139–129139. 19 indexed citations

Lay, Thorne, Lingling Ye, Zhenbo Wu, & Hiroo Kanamori. (2020). Macrofracturing of Oceanic Lithosphere in Complex Large Earthquake Sequences. Journal of Geophysical Research Solid Earth. 125(10). 5 indexed citations

Bai, Zhiming, et al.. (2020). Cenozoic magmatic activity and oblique uplifting of the Ailao Mountain: Evidence from a short-period dense seismic array. Science China Earth Sciences. 63(9). 1294–1308. 12 indexed citations

Liang, Chuntao, et al.. (2019). The Complex Velocity Variation Induced by the Precipitation and the 2018 Eruption of the Kilauea Volcano in Hawaii Revealed by Ambient Noise. Seismological Research Letters. 90(6). 2154–2164. 8 indexed citations

Wu, Zhenbo, Thorne Lay, & Lingling Ye. (2019). Shallow Megathrust Slip During Large Earthquakes That Have High P Coda Levels. Journal of Geophysical Research Solid Earth. 125(1). 2 indexed citations

10.

Li, Tong, et al.. (2018). Dual‐polarised and ultra‐thin broadband AAMCs for both P and L bands applications. IET Microwaves Antennas & Propagation. 13(2). 185–189. 18 indexed citations

11.

Liu, Zhen, Xiaobo Tian, Rui Gao, et al.. (2017). New images of the crustal structure beneath eastern Tibet from a high-density seismic array. Earth and Planetary Science Letters. 480. 33–41. 65 indexed citations

12.

Wu, Zhenbo, et al.. (2017). Crustal shear wave velocity structure in the northeastern Tibet based on the Neighbourhood algorithm inversion of receiver functions. Geophysical Journal International. 212(3). 1920–1931. 7 indexed citations

13.

Wu, Chenglong, Tao Xu, José Badal, Zhenbo Wu, & Jiwen Teng. (2015). Seismic anisotropy across the Kunlun fault and their implications for northward transforming lithospheric deformation in northeastern Tibet. Tectonophysics. 659. 91–101. 18 indexed citations

14.

Wu, Zhenbo, Tao Xu, José Badal, et al.. (2015). Crustal shear-wave velocity structure of northeastern Tibet revealed by ambient seismic noise and receiver functions. Gondwana Research. 41. 400–410. 15 indexed citations

15.

Cai, Yongjiu, et al.. (2014). Community structure and decadal changes in macrozoobenthic assemblages in Lake Poyang, the largest freshwater lake in China. Knowledge and Management of Aquatic Ecosystems. 9–9. 21 indexed citations

16.

Zhang, Zhongjie, Yanghua Wang, G. A. Houseman, et al.. (2014). The Moho beneath western Tibet: Shear zones and eclogitization in the lower crust. Earth and Planetary Science Letters. 408. 370–377. 78 indexed citations

17.

Xu, Tao, Fei Li, Zhenbo Wu, et al.. (2014). A successive three-point perturbation method for fast ray tracing in complex 2D and 3D geological models. Tectonophysics. 627. 72–81. 31 indexed citations

18.

Xu, Tao, Zhenbo Wu, Zhongjie Zhang, et al.. (2013). Crustal structure across the Kunlun fault from passive source seismic profiling in East Tibet. Tectonophysics. 627. 98–107. 43 indexed citations

19.

Li, Fei, Tao Xu, Minghui Zhang, et al.. (2013). Seismic traveltime inversion of 3D velocity model with triangulated interfaces. Earthquake Science. 27(2). 127–136. 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.

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