Han Long

771 citations
69 papers · 559 · h-index 14

Impact in

Papers in

Han Long

57 papers receiving 539 citations

Peers

Han Long
Comparison fields: 5 of 91
  • Electrochemistry 40
  • Electrical and Electronic Engineering 286
  • Renewable Energy, Sustainability and the Environment 62
  • Computer Vision and Pattern Recognition 71
  • Polymers and Plastics 43
Replace Yanxia Liu with:
Yanxia Liu China
Ziyun Li United States
Yunong Zhang China
Pingping Xu China
Xiaolu Wang China
Jiaxing Wang China
Yanxia Zhao China
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Citations per field
00.5×4.2×
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Citations per year

Countries citing papers authored by Han Long

Since Specialization
Citations

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

Fields of papers citing papers by Han Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Han Long, 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 Han Long Line = papers co-authored together Han Long links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202061
2 202453
3 202048
4 202338
5 201827
6 201626
7 202326
8 201425
9 202423
10 202316
11 202416
12 202415
13 202415
14 202214
15 202212
16 201310
17 20228
18 20228
19 20108
20
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
20067

About Han Long

Han Long is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Aerospace Engineering, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 69 papers that have together received 559 indexed citations. Recurring topics across this work include Fuel Cells and Related Materials (8 papers), Optical Network Technologies (7 papers), Membrane-based Ion Separation Techniques (7 papers), Robotic Path Planning Algorithms (7 papers), Electrocatalysts for Energy Conversion (6 papers), Reinforcement Learning in Robotics (5 papers), UAV Applications and Optimization (5 papers) and Advanced Optical Network Technologies (5 papers). The work is most often cited by research in Electrochemistry (40 citations), Electrical and Electronic Engineering (286 citations), Renewable Energy, Sustainability and the Environment (62 citations), Computer Vision and Pattern Recognition (71 citations) and Polymers and Plastics (43 citations). Han Long has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Shoutao Gong, Fengxiang Zhang, Dongmei Deng, Liqiang Luo, Xiaoming Yan, Li Tang, Gaohong He, Quan Jin, Zhigang Zeng and Huan Ke. Their work appears in journals such as Applied Sciences, Journal of Membrane Science, Journal of Materials Chemistry A, Neural Networks and Journal of Modern Optics.

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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