Min Kong

757 citations
39 papers · 415 indexed · h-index 9
Topics
Metaheuristic Optimization Algorithms Research (9 papers)Quantum Information and Cryptography (5 papers)Quantum Computing Algorithms and Architecture (4 papers)
Partner nations
ChinaMalaysiaMacao

In The Last Decade

Min Kong

34 papers receiving 396 citations

Peers

Min Kong
Comparison fields: 5 of 66
  • Computer Vision and Pattern Recognition 156
  • Artificial Intelligence 147
  • Industrial and Manufacturing Engineering 89
  • Electrical and Electronic Engineering 55
  • Computer Networks and Communications 45
Replace Taifan Quan with:
Taifan Quan China
Keisuke Kameyama Japan
Xiaolong Ma United States
Xiwei Dong China
Alan Crispin United Kingdom
Fazhi He China
Giulio Gambardella Italy
Shulin Zeng China
Chi‐Chia Sun Taiwan
Min Kong relative to Taifan Quan China Taifan Quan's profile →
Citations per field
00.5×5.7×
Taifan Quan · 1×
Citations per year

Countries citing papers authored by Min Kong

Since Specialization
Citations

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

Fields of papers citing papers by Min Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Kong

This figure shows the co-authorship network connecting the top 25 collaborators of Min Kong. A scholar is included among the top collaborators of Min Kong 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 Min Kong. Min Kong 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
#WorkIndexed citations
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4 11
5 3
6 2
7 0
8 16
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14 2
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18 1
19
Various Problems of Artificial Intelligence-Apply the Particle Swarm Optimization to the Multidimensional Knapsack Problem
1
20
A Convergence Proof for the Ant Colony Optimization Algorithms.
0

About Min Kong

Min Kong is a scholar working on Industrial and Manufacturing Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 39 papers that have together received 415 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (9 papers), Quantum Information and Cryptography (5 papers) and Quantum Computing Algorithms and Architecture (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (89 citations), Computer Vision and Pattern Recognition (156 citations) and Computational Mathematics (4 citations). Min Kong has collaborated with scholars based in China, Malaysia and Macao. Frequent co-authors include Peng Tian, Yu‐Cheng Kao, Bin Luo, Si-Bao Chen, Haifeng Zhao, Jinzhong Zhang, Tan Zhang, Duansong Wang, Yourui Huang and Gang Zhang. Their work appears in journals such as Scientific Reports, IEEE Access and Applied Thermal Engineering.

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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