Nanlin Jin

1.2k citations
49 papers · 652 · h-index 12

Impact in

Papers in

    • Data Stream Mining Techniques 9
    • Anomaly Detection Techniques and Applications 7
    • Machine Learning and Data Classification 6
    • Evolutionary Algorithms and Applications 4
    • Fault Detection and Control Systems 4
    • Machine Fault Diagnosis Techniques 4

Nanlin Jin

40 papers receiving 622 citations

Peers

Nanlin Jin
Comparison fields: 5 of 106
  • Management Science and Operations Research 77
  • Artificial Intelligence 172
  • Control and Systems Engineering 119
  • Global and Planetary Change 79
  • Electrical and Electronic Engineering 197
Replace Mukta Paliwal with:
Mukta Paliwal India
Roselina Sallehuddin Malaysia
Usha A. Kumar India
Miomir Stanković Serbia
Sulaiman Khan Pakistan
İnci Batmaz Türkiye
Minggang Wang China
Panagiotis Tzionas Greece
Sajid Siraj United Kingdom
Bernady O. Apduhan Japan
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Citations per field
00.5×3.7×
Mukta Paliwal · 1×
Citations per year

Countries citing papers authored by Nanlin Jin

Since Specialization
Citations

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

Fields of papers citing papers by Nanlin Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nanlin Jin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nanlin Jin Line = papers co-authored together Nanlin Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007114
2 201696
3 202194
4 201964
5 201427
6 201922
7 200919
8 201415
9 202214
10 200614
11 202314
12
Population Based Incremental Learning Versus Genetic Algorithms: Iterated Prisoners Dilemma
200413
13 202111
14 202210
15 202310
16 20089
17 20189
18 20198
19 20058
20 20078

About Nanlin Jin

Nanlin Jin is a scholar working on Artificial Intelligence, Control and Systems Engineering, Management Science and Operations Research, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 652 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (9 papers), Anomaly Detection Techniques and Applications (7 papers), Machine Learning and Data Classification (6 papers), Fault Detection and Control Systems (4 papers), Machine Fault Diagnosis Techniques (4 papers), Evolutionary Algorithms and Applications (4 papers), Auction Theory and Applications (4 papers) and Game Theory and Voting Systems (4 papers). The work is most often cited by research in Management Science and Operations Research (77 citations), Artificial Intelligence (172 citations), Control and Systems Engineering (119 citations), Global and Planetary Change (79 citations) and Electrical and Electronic Engineering (197 citations). Nanlin Jin has collaborated with scholars based in United Kingdom, China and Chile. Frequent co-authors include Peter Flach, Aihua Zhang, Zhiwei Gao, Reem Alotaibi, Edward Tsang, Klaus Hubacek, Claire H. Quinn, Mark S. Reed, Joseph Holden and Tim Burt. Their work appears in journals such as IEEE Transactions on Industrial Informatics, Applied Soft Computing, Geomatics Natural Hazards and Risk, Computational Economics and Computers in Industry.

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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