Jun-Hong Zhou

587 total citations
23 papers, 468 citations indexed

About

Jun-Hong Zhou is a scholar working on Control and Systems Engineering, Mechanical Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Jun-Hong Zhou has authored 23 papers receiving a total of 468 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Control and Systems Engineering, 9 papers in Mechanical Engineering and 8 papers in Industrial and Manufacturing Engineering. Recurrent topics in Jun-Hong Zhou's work include Fault Detection and Control Systems (11 papers), Machine Fault Diagnosis Techniques (10 papers) and Advanced machining processes and optimization (8 papers). Jun-Hong Zhou is often cited by papers focused on Fault Detection and Control Systems (11 papers), Machine Fault Diagnosis Techniques (10 papers) and Advanced machining processes and optimization (8 papers). Jun-Hong Zhou collaborates with scholars based in Singapore, United States and Australia. Jun-Hong Zhou's co-authors include Chee Khiang Pang, Jian‐Xin Xu, Z.W. Zhong, Frank L. Lewis, Xiang Li, Xiang Li, Huan Xu, Geok Soon Hong, Chong Zhang and Keng Soon Woon and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and IEEE Transactions on Industrial Informatics.

In The Last Decade

Jun-Hong Zhou

22 papers receiving 456 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jun-Hong Zhou Singapore	10	265	173	156	105	61	23	468
Lucas Costa Brito Brazil	6	233 0.9×	211 1.2×	118 0.8×	115 1.1×	90 1.5×	9	453
Yang Fu China	12	306 1.2×	203 1.2×	164 1.1×	98 0.9×	86 1.4×	19	510
Wen-An Yang China	12	167 0.6×	105 0.6×	101 0.6×	119 1.1×	51 0.8×	28	373
Tao Zan China	12	326 1.2×	200 1.2×	55 0.4×	110 1.0×	46 0.8×	54	538
Zhuo Long China	14	166 0.6×	399 2.3×	143 0.9×	54 0.5×	89 1.5×	42	630
Chengying Zhao China	13	233 0.9×	339 2.0×	67 0.4×	56 0.5×	56 0.9×	30	544
Xiaoqing Cheng China	10	133 0.5×	197 1.1×	71 0.5×	48 0.5×	40 0.7×	34	396
Moussa Hamadache South Korea	11	274 1.0×	398 2.3×	60 0.4×	56 0.5×	57 0.9×	24	556
M. Saimurugan India	10	237 0.9×	347 2.0×	51 0.3×	41 0.4×	41 0.7×	32	465

Countries citing papers authored by Jun-Hong Zhou

Since Specialization

Citations

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

Fields of papers citing papers by Jun-Hong Zhou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun-Hong Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Jun-Hong Zhou. A scholar is included among the top collaborators of Jun-Hong Zhou 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 Jun-Hong Zhou. Jun-Hong Zhou 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

Zhou, Jun-Hong, et al.. (2021). A Clinical Study on Gestational Diabetes Mellitus and the Hearing of Newborns. Diabetes Metabolic Syndrome and Obesity. Volume 14. 2879–2882. 4 indexed citations

Zhou, Jun-Hong, et al.. (2017). Gaussian mixture model for new fault categories diagnosis. 1–6. 2 indexed citations

Zhou, Jun-Hong, et al.. (2017). Gaussian Mixture Model Using Semisupervised Learning for Probabilistic Fault Diagnosis Under New Data Categories. IEEE Transactions on Instrumentation and Measurement. 66(4). 723–733. 54 indexed citations

Zhou, Jun-Hong, et al.. (2016). New types of faults detection and diagnosis using a mixed soft & hard clustering framework. 1–6. 9 indexed citations

Luo, Ming, et al.. (2014). Predictive maintenance decision using statistical linear regression and kernel methods. 1–6. 12 indexed citations

Xu, Jian‐Xin, et al.. (2013). Multimodal Hidden Markov Model-Based Approach for Tool Wear Monitoring. IEEE Transactions on Industrial Electronics. 61(6). 2900–2911. 57 indexed citations

Xu, Jian‐Xin, et al.. (2012). Feature selection for tool wear monitoring: A comparative study. National University of Singapore. 58. 1230–1235. 5 indexed citations

Li, Xiang, et al.. (2012). Hybrid rebalancing approach to handle imbalanced dataset for fault diagnosis in manufacturing systems. 8. 1224–1229. 5 indexed citations

Xu, Jian‐Xin, et al.. (2012). A Physically Segmented Hidden Markov Model Approach for Continuous Tool Condition Monitoring: Diagnostics and Prognostics. IEEE Transactions on Industrial Informatics. 8(4). 964–973. 96 indexed citations

10.

Xu, Jian‐Xin, et al.. (2011). A multi-modal hidden Markov model based approach for continuous health assessment in machinery systems. National University of Singapore. 58. 2294–2299. 1 indexed citations

11.

Xu, Jian‐Xin, et al.. (2011). Continuous health condition monitoring: A single Hidden Semi-Markov Model approach. National University of Singapore. 1–10. 17 indexed citations

12.

Pang, Chee Khiang, Jun-Hong Zhou, Z.W. Zhong, & Frank L. Lewis. (2010). Tool wear forecast using Dominant Feature Identification of acoustic emissions. National University of Singapore. 1063–1068. 4 indexed citations

13.

Zhou, Jun-Hong, Chee Khiang Pang, Z.W. Zhong, & Frank L. Lewis. (2010). Tool Wear Monitoring Using Acoustic Emissions by Dominant-Feature Identification. IEEE Transactions on Instrumentation and Measurement. 60(2). 547–559. 127 indexed citations

14.

Jahromi, Amin Torabi, Er Meng Joo, Lian-Yin Zhai, et al.. (2009). A survey on artificial intelligence technologies in modeling of High Speed end-milling processes. 320–325. 13 indexed citations

15.

Zhang, Danhong, et al.. (2009). iDiagnosis & prognosis for supporting of manufacture. 4. 638–643.

16.

Zhou, Jun-Hong, et al.. (2009). iDiagnosis & Prognosis - An intelligent platform for complex manufacturing. 4. 405–410. 1 indexed citations

17.

Ren, Wei, Gang Chen, Zhonghua Yang, et al.. (2008). Semantic enhanced rule driven workflow execution in Collaborative Virtual Enterprise. Griffith Research Online (Griffith University, Queensland, Australia). 910–915. 4 indexed citations

18.

Arogeti, Shai, et al.. (2008). Mode Tracking of Hybrid Systems in FDI Framework. 2289. 841–846. 10 indexed citations

19.

Chaudhari, Narendra S., et al.. (2008). Time series prediction using principal feature analysis. 292–297. 5 indexed citations

20.

Luo, Ming, et al.. (2008). Agent-based service-oriented dynamic resource allocation. 1. 921–926. 4 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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