Chuan Lin

2.6k total citations
101 papers, 1.9k citations indexed

About

Chuan Lin is a scholar working on Computer Networks and Communications, Ocean Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Chuan Lin has authored 101 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Computer Networks and Communications, 28 papers in Ocean Engineering and 27 papers in Electrical and Electronic Engineering. Recurrent topics in Chuan Lin's work include Underwater Vehicles and Communication Systems (28 papers), IoT and Edge/Fog Computing (15 papers) and Energy Efficient Wireless Sensor Networks (13 papers). Chuan Lin is often cited by papers focused on Underwater Vehicles and Communication Systems (28 papers), IoT and Edge/Fog Computing (15 papers) and Energy Efficient Wireless Sensor Networks (13 papers). Chuan Lin collaborates with scholars based in China, United Kingdom and United States. Chuan Lin's co-authors include Guangjie Han, Jiaxin Du, Yuanguo Bi, Lei Shu, Mohsen Guizani, Miguel Martínez-García, Naixue Xiong, Yan Peng, Yanxiang He and Syed Bilal Hussain Shah and has published in prestigious journals such as Journal of Applied Physics, IEEE Transactions on Geoscience and Remote Sensing and IEEE Access.

In The Last Decade

Chuan Lin

92 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chuan Lin China 26 962 553 481 333 261 101 1.9k
Tingting Yang China 24 996 1.0× 766 1.4× 348 0.7× 417 1.3× 414 1.6× 129 2.1k
Feng Wang China 28 1.1k 1.1× 638 1.2× 269 0.6× 149 0.4× 266 1.0× 145 2.3k
Xin Su China 20 431 0.4× 797 1.4× 327 0.7× 341 1.0× 289 1.1× 131 1.6k
Saleh Alghamdi Saudi Arabia 28 954 1.0× 538 1.0× 189 0.4× 136 0.4× 367 1.4× 41 2.0k
Qinghai Yang China 25 1.2k 1.2× 1.1k 2.1× 337 0.7× 378 1.1× 186 0.7× 282 2.4k
Saad Qaisar Pakistan 25 1.3k 1.3× 1.4k 2.5× 540 1.1× 118 0.4× 285 1.1× 81 2.6k
Thomas Newe Ireland 22 843 0.9× 496 0.9× 161 0.3× 103 0.3× 282 1.1× 122 1.8k
Qi Han United States 21 900 0.9× 801 1.4× 199 0.4× 82 0.2× 347 1.3× 129 2.1k
Bang Wang China 30 1.9k 2.0× 1.9k 3.4× 549 1.1× 322 1.0× 544 2.1× 212 3.5k

Countries citing papers authored by Chuan Lin

Since Specialization
Citations

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

Fields of papers citing papers by Chuan Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chuan Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Chuan Lin. A scholar is included among the top collaborators of Chuan Lin 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 Chuan Lin. Chuan Lin 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
1.
Su, Yan, et al.. (2025). Complex cross-regional landslide susceptibility mapping by multi-source domain transfer learning. Geoscience Frontiers. 16(4). 102053–102053. 1 indexed citations
2.
Lin, Chuan, et al.. (2024). Can the China–Europe Railway Express reduce carbon dioxide emissions? New mechanism of the manufacturing industry substitution effect. Economic Analysis and Policy. 82. 1384–1405. 6 indexed citations
3.
Su, Yan, et al.. (2024). Feature adaptation for landslide susceptibility assessment in “no sample” areas. Gondwana Research. 131. 1–17. 11 indexed citations
4.
Du, Jiaxin, Guangjie Han, Chuan Lin, Xiangjie Kong, & Guojiang Shen. (2024). An Autonomous Underwater Vehicle-Assisted Adaptive Trust Prediction Model for UASNs. IEEE Transactions on Intelligent Vehicles. 10(3). 2027–2036. 4 indexed citations
5.
Han, Guangjie, et al.. (2024). Underwater Target Tracking Based on Hierarchical Software-Defined Multi-AUV Reinforcement Learning: A Multi-AUV Advantage-Attention Actor-Critic Approach. IEEE Transactions on Mobile Computing. 23(12). 13639–13653. 2 indexed citations
6.
Han, Guangjie, et al.. (2024). Multiscale BLS-Based Lightweight Prediction Model for Remaining Useful Life of Aero-Engine. IEEE Transactions on Reliability. 73(4). 1757–1767. 13 indexed citations
7.
Xu, Xuelu, et al.. (2024). Unintended environmental gains: The impact of China–Europe Railway Express on carbon dioxide emissions in China. Transport Policy. 153. 127–140. 10 indexed citations
8.
Han, Guangjie, et al.. (2024). Underwater Multiple AUV Cooperative Target Tracking Based on Minimal Reward Participation-Embedded MARL. IEEE Transactions on Mobile Computing. 24(5). 4169–4182. 1 indexed citations
9.
Han, Guangjie, et al.. (2023). Distributional Soft Actor-Critic-Based Multi-AUV Cooperative Pursuit for Maritime Security Protection. IEEE Transactions on Intelligent Transportation Systems. 25(6). 6049–6060. 20 indexed citations
10.
Han, Guangjie, et al.. (2023). A Scheme for Cooperative-Escort Multi-Submersible Intelligent Transportation System Based on SDN-Enabled Underwater IoV. IEEE Transactions on Intelligent Transportation Systems. 24(11). 13472–13485. 6 indexed citations
11.
Shao, Shiliang, Guangjie Han, Ting Wang, et al.. (2023). EEG-Based Mental Workload Classification Method Based on Hybrid Deep Learning Model Under IoT. IEEE Journal of Biomedical and Health Informatics. 28(5). 2536–2546. 14 indexed citations
12.
13.
Li, Feiyan, et al.. (2023). SDN-QLTR: Q-Learning-Assisted Trust Routing Scheme for SDN-Based Underwater Acoustic Sensor Networks. IEEE Internet of Things Journal. 11(6). 10682–10694. 9 indexed citations
14.
Jiang, Jinfang, Chuan Lin, Guangjie Han, et al.. (2022). How AI-enabled SDN technologies improve the security and functionality of industrial IoT network: Architectures, enabling technologies, and opportunities. Digital Communications and Networks. 9(6). 1351–1362. 22 indexed citations
15.
Qin, Zhenquan, Zhonghao Liu, Guangjie Han, et al.. (2021). Distributed UAV-BSs Trajectory Optimization for User-Level Fair Communication Service With Multi-Agent Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology. 70(12). 12290–12301. 55 indexed citations
16.
Qin, Zhenquan, et al.. (2021). Optimal Workload Allocation for Edge Computing Network Using Application Prediction. Wireless Communications and Mobile Computing. 2021(1). 8 indexed citations
17.
Liu, Xin, et al.. (2020). Joint Resource Optimization for UAV-Enabled Multichannel Internet of Things Based on Intelligent Fog Computing. IEEE Transactions on Network Science and Engineering. 8(4). 2814–2824. 18 indexed citations
18.
Peng, Haixia, Hai Zhao, & Chuan Lin. (2013). An Web Client System Design and Implementation for IOS Platform. Journal of Software Engineering and Applications. 6(1). 38–42.
19.
Zhang, Min, et al.. (2003). THUIR at TREC 2003: Novelty, Robust and Web *. Text REtrieval Conference. 556–567. 13 indexed citations
20.
Zhang, Min, Ruihua Song, Chuan Lin, et al.. (2002). THU TREC 2002: Novelty Track Experiments.. Text REtrieval Conference. 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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