Zhangjun Wu

873 total citations
24 papers, 640 citations indexed

About

Zhangjun Wu is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Zhangjun Wu has authored 24 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Control and Systems Engineering, 11 papers in Artificial Intelligence and 8 papers in Computer Networks and Communications. Recurrent topics in Zhangjun Wu's work include Fault Detection and Control Systems (6 papers), Machine Fault Diagnosis Techniques (6 papers) and Distributed and Parallel Computing Systems (5 papers). Zhangjun Wu is often cited by papers focused on Fault Detection and Control Systems (6 papers), Machine Fault Diagnosis Techniques (6 papers) and Distributed and Parallel Computing Systems (5 papers). Zhangjun Wu collaborates with scholars based in China, Australia and United States. Zhangjun Wu's co-authors include Zhiwei Ni, Xiao Liu, Lichuan Gu, Yun Yang, Dong Yuan, Gang Wang, Jinjun Chen, Chang Zhang, Yuanchun Jiang and Haidong Shao and has published in prestigious journals such as Applied Soft Computing, Reliability Engineering & System Safety and IEEE Sensors Journal.

In The Last Decade

Zhangjun Wu

23 papers receiving 599 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhangjun Wu China	13	441	416	142	107	99	24	640
Yao Dai China	11	151 0.3×	266 0.6×	10 0.1×	76 0.7×	37 0.4×	22	498
Xiaojun Ruan United States	14	632 1.4×	722 1.7×	24 0.2×	87 0.8×	37 0.4×	59	874
Longxin Zhang China	7	291 0.7×	337 0.8×	21 0.1×	69 0.6×	29 0.3×	13	491
Thomas Rausch Austria	11	428 1.0×	540 1.3×	32 0.2×	100 0.9×	29 0.3×	28	717
Rohaya Latip Malaysia	14	333 0.8×	422 1.0×	28 0.2×	128 1.2×	12 0.1×	62	607
Weizhong Qiang China	12	246 0.6×	361 0.9×	12 0.1×	233 2.2×	42 0.4×	63	606
Liying Li China	11	170 0.4×	297 0.7×	9 0.1×	99 0.9×	27 0.3×	47	537
Supun Kamburugamuve United States	11	157 0.4×	242 0.6×	32 0.2×	70 0.7×	32 0.3×	24	321
Ashley Chonka Australia	10	315 0.7×	423 1.0×	13 0.1×	246 2.3×	23 0.2×	19	611

Countries citing papers authored by Zhangjun Wu

Since Specialization

Citations

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

Fields of papers citing papers by Zhangjun Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhangjun Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhangjun Wu. A scholar is included among the top collaborators of Zhangjun 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 Zhangjun Wu. Zhangjun 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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20 of 20 papers shown

Wu, Zhangjun, et al.. (2024). A holistic semi-supervised method for imbalanced fault diagnosis of rotational machinery with out-of-distribution samples. Reliability Engineering & System Safety. 250. 110297–110297. 23 indexed citations

Wu, Zhangjun, et al.. (2024). An End-to-end Deep Clustering Method with Consistency and Complementarity Attention Mechanism for Multisensor Fault Diagnosis. Applied Soft Computing. 158. 111594–111594. 9 indexed citations

Wang, Gang, et al.. (2023). An ensemble method with DenseNet and evidential reasoning rule for machinery fault diagnosis under imbalanced condition. Measurement. 214. 112806–112806. 23 indexed citations

Wu, Zhangjun, et al.. (2023). Fusing global features and local information for COVID-19 detection with X-ray images. Signal Image and Video Processing. 18(3). 2643–2657. 1 indexed citations

Wang, Gang, Yanan Zhang, Ming-Feng Lu, & Zhangjun Wu. (2023). Hierarchical graph neural network with adaptive cross-graph fusion for remaining useful life prediction. Measurement Science and Technology. 34(5). 55112–55112. 12 indexed citations

Wang, Gang, et al.. (2022). A denoising and multiscale residual deep network for soft sensor modeling of industrial processes. Measurement Science and Technology. 33(10). 105117–105117. 14 indexed citations

Wang, Gang, et al.. (2022). A novel random subspace method considering complementarity between unsupervised and supervised deep representation features for soft sensors. Measurement Science and Technology. 33(10). 105119–105119. 1 indexed citations

Wang, Gang, et al.. (2022). Triple Attention-based deep convolutional recurrent network for soft sensors. Measurement. 202. 111897–111897. 8 indexed citations

Peng, Peng, Zhiwei Ni, Zhangjun Wu, Xuhui Zhu, & Pingfan Xia. (2022). Research on incentive strategy based on service quality in spatial crowdsourcing task allocation. Journal of Intelligent & Fuzzy Systems. 43(5). 5551–5566. 1 indexed citations

10.

Zhu, Xuhui, et al.. (2020). Ensemble pruning of ELM via migratory binary glowworm swarm optimization and margin distance minimization. Neural Processing Letters. 52(3). 2043–2067. 3 indexed citations

11.

Ni, Zhiwei, et al.. (2020). Formulating monitoring strategy based on multiple SLA parameters for multi-tenant service-based systems. International Journal of Web and Grid Services. 16(2). 200–200.

12.

Ni, Zhiwei, et al.. (2013). A Similarity Measures Algorithm for CBR Based on Matrix Iterative Learning. International Journal of Applied Mathematics & Statistics. 43(13). 271–280. 1 indexed citations

13.

Wu, Zhangjun, Xiao Liu, Zhiwei Ni, Dong Yuan, & Yun Yang. (2011). A market-oriented hierarchical scheduling strategy in cloud workflow systems. The Journal of Supercomputing. 63(1). 256–293. 194 indexed citations

14.

Liu, Xiao, Zhiwei Ni, Zhangjun Wu, et al.. (2010). A novel general framework for automatic and cost-effective handling of recoverable temporal violations in scientific workflow systems. Journal of Systems and Software. 84(3). 492–509. 25 indexed citations

15.

Liu, Xiao, Zhiwei Ni, Dong Yuan, et al.. (2010). A novel statistical time-series pattern based interval forecasting strategy for activity durations in workflow systems. Journal of Systems and Software. 84(3). 354–376. 46 indexed citations

16.

Liu, Xiao, Zhiwei Ni, Zhangjun Wu, et al.. (2010). An Effective Framework of Light-Weight Handling for Three-Level Fine-Grained Recoverable Temporal Violations in Scientific Workflows. Figshare. 4001. 43–50. 3 indexed citations

17.

Liu, Xiao, Jinjun Chen, Zhangjun Wu, et al.. (2010). Handling Recoverable Temporal Violations in Scientific Workflow Systems: A Workflow Rescheduling Based Strategy. Swinburne Research Bank (Swinburne University of Technology). 534–537. 18 indexed citations

18.

Wu, Zhangjun, Zhiwei Ni, Chang Zhang, & Lichuan Gu. (2009). A Novel PSO for Multi-stage Portfolio Planning. 19. 71–77. 2 indexed citations

19.

Zhang, Chang, Zhiwei Ni, Zhangjun Wu, & Lichuan Gu. (2009). A Novel Swarm Model With Quasi-oppositional Particle. 325–330. 28 indexed citations

20.

Wu, Zhangjun, Zhiwei Ni, Chang Zhang, & Lichuan Gu. (2008). Opposition based comprehensive learning particle swarm optimization. 1013–1019. 18 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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