Cong Guan

1.9k total citations · 1 hit paper
41 papers, 1.5k citations indexed

About

Cong Guan is a scholar working on Control and Systems Engineering, Environmental Engineering and Materials Chemistry. According to data from OpenAlex, Cong Guan has authored 41 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Control and Systems Engineering, 12 papers in Environmental Engineering and 10 papers in Materials Chemistry. Recurrent topics in Cong Guan's work include Maritime Transport Emissions and Efficiency (12 papers), Machine Fault Diagnosis Techniques (9 papers) and Fault Detection and Control Systems (8 papers). Cong Guan is often cited by papers focused on Maritime Transport Emissions and Efficiency (12 papers), Machine Fault Diagnosis Techniques (9 papers) and Fault Detection and Control Systems (8 papers). Cong Guan collaborates with scholars based in China, Singapore and United Kingdom. Cong Guan's co-authors include Hui Chen, Zehui Zhang, Kean Wang, Ruihan Wang, Wenfeng Gong, Γεράσιμος Θεοτοκάτος, Haibo Gao, Chun Yang, Chang Ming Li and Xiaogang Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACS Nano and Energy & Environmental Science.

In The Last Decade

Cong Guan

34 papers receiving 1.5k citations

Hit Papers

A Novel Deep Learning Method for Intelligent Fault Diagno... 2019 2026 2021 2023 2019 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Novel Deep Learning Method for Intelligent Fault Diagnosis of Rotating Machinery Based on Improved CNN-SVM and Multichannel Data Fusion
    2019 185 citations Hui Chen, Ruihan Wang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cong Guan China 22 398 344 342 299 282 41 1.5k
Niranjan Sahoo India 25 303 0.8× 257 0.7× 524 1.5× 395 1.3× 330 1.2× 118 2.0k
Ramizi Mohamed Malaysia 13 264 0.7× 242 0.7× 1.0k 2.9× 264 0.9× 240 0.9× 74 1.6k
T. El Rhafiki Morocco 26 227 0.6× 213 0.6× 542 1.6× 1.7k 5.5× 148 0.5× 64 2.9k
Mohammad Alkhedher United Arab Emirates 20 374 0.9× 85 0.2× 660 1.9× 318 1.1× 343 1.2× 165 1.6k
Ssennoga Twaha United Kingdom 19 579 1.5× 290 0.8× 823 2.4× 371 1.2× 176 0.6× 26 2.2k
Mohamad Kamarol Mohd Jamil Malaysia 19 548 1.4× 257 0.7× 1.1k 3.2× 194 0.6× 160 0.6× 131 1.7k
Yingchao Zhang China 22 151 0.4× 199 0.6× 439 1.3× 214 0.7× 99 0.4× 128 1.4k
Prabhu Paramasivam India 23 323 0.8× 80 0.2× 346 1.0× 476 1.6× 175 0.6× 183 1.7k
Min Oh South Korea 20 338 0.8× 173 0.5× 298 0.9× 646 2.2× 167 0.6× 52 1.5k
Menghan Li China 24 607 1.5× 91 0.3× 422 1.2× 288 1.0× 514 1.8× 142 2.1k

Countries citing papers authored by Cong Guan

Since Specialization
Citations

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

Fields of papers citing papers by Cong Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cong Guan

This figure shows the co-authorship network connecting the top 25 collaborators of Cong Guan. A scholar is included among the top collaborators of Cong Guan 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 Cong Guan. Cong Guan 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
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Guan, Cong & Osamu Yoshie. (2025). CLIP-driven rain perception: Adaptive deraining with pattern-aware network routing and mask-guided cross-attention. Pattern Recognition. 173. 112886–112886.
3.
Fan, Ailong, Peng Wu, Yang Liu, et al.. (2025). LSTM-augmented DRL for generalisable energy management of hydrogen-hybrid ship propulsion systems. eTransportation. 25. 100442–100442. 1 indexed citations
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Diao, Xuemei, Yang Li, Peng Wang, et al.. (2024). Nickel-Induced Dual Carbon Networks Encapsulating Phase Change Materials for Photothermal Conversion and Storage. ACS Applied Materials & Interfaces. 16(48). 66192–66200. 7 indexed citations
6.
Wang, Ruihan, Hui Chen, & Cong Guan. (2023). A self-supervised contrastive learning framework with the nearest neighbors matching for the fault diagnosis of marine machinery. Ocean Engineering. 270. 113437–113437. 25 indexed citations
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Zhou, Yi, et al.. (2023). Three-Phase Asynchronous Motor Fault Diagnosis Using Attention Mechanism and Hybrid CNN-MLP By Multi-Sensor Information. IEEE Access. 11. 98402–98414. 12 indexed citations
9.
Guan, Cong, et al.. (2023). Improvement and Optimization Configuration of Inland Ship Power and Propulsion System. Journal of Marine Science and Engineering. 11(1). 135–135. 16 indexed citations
10.
Chen, Hui, et al.. (2023). Energy Management Optimization of Fuel Cell Hybrid Ship Based on Particle Swarm Optimization Algorithm. Energies. 16(3). 1373–1373. 21 indexed citations
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Wang, Ruihan, et al.. (2022). Fault diagnosis of marine diesel engines based on graph convolutional network under unbalanced datasets. SHILAP Revista de lepidopterología. 2 indexed citations
14.
Wang, Ruihan, Hui Chen, & Cong Guan. (2022). DPGCN Model: A Novel Fault Diagnosis Method for Marine Diesel Engines Based on Imbalanced Datasets. IEEE Transactions on Instrumentation and Measurement. 72. 1–11. 24 indexed citations
15.
Wang, Ruihan, Hui Chen, & Cong Guan. (2021). Condition monitoring method for marine engine room equipment based on machine learning. SHILAP Revista de lepidopterología.
16.
Wang, Ruihan, Hui Chen, & Cong Guan. (2021). A Bayesian inference-based approach for performance prognostics towards uncertainty quantification and its applications on the marine diesel engine. ISA Transactions. 118. 159–173. 37 indexed citations
17.
Θεοτοκάτος, Γεράσιμος, Athanasios Rentizelas, Cong Guan, & Ivica Ančić. (2020). Waste heat recovery steam systems techno-economic and environmental investigation for ocean-going vessels considering actual operating profiles. Journal of Cleaner Production. 267. 121837–121837. 24 indexed citations
18.
Guan, Cong, Γεράσιμος Θεοτοκάτος, & Hui Chen. (2015). Analysis of Two Stroke Marine Diesel Engine Operation Including Turbocharger Cut-Out by Using a Zero-Dimensional Model. Energies. 8(6). 5738–5764. 43 indexed citations
19.
Guan, Cong, Leslie S. Loo, Kean Wang, & Chun Yang. (2010). Methane storage in carbon pellets prepared via a binderless method. Energy Conversion and Management. 52(2). 1258–1262. 31 indexed citations
20.
Wang, Yi, An Li, Kean Wang, et al.. (2010). Reversible hydrogen storage of multi-wall carbon nanotubes doped with atomically dispersed lithium. Journal of Materials Chemistry. 20(31). 6490–6490. 34 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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