Cheng Xing

832 total citations · 1 hit paper
17 papers, 546 citations indexed

About

Cheng Xing is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Cheng Xing has authored 17 papers receiving a total of 546 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Control and Systems Engineering. Recurrent topics in Cheng Xing's work include Metaheuristic Optimization Algorithms Research (4 papers), Fault Detection and Control Systems (3 papers) and Machine Learning and ELM (2 papers). Cheng Xing is often cited by papers focused on Metaheuristic Optimization Algorithms Research (4 papers), Fault Detection and Control Systems (3 papers) and Machine Learning and ELM (2 papers). Cheng Xing collaborates with scholars based in China, South Korea and United States. Cheng Xing's co-authors include Zhongkai Zhao, Yihan Xiao, Hezheng Lin, Xiangyu Wu, Dong Shen, Jie‐Sheng Wang, Wei Xie, Shasha Guo, Lingfeng Zhu and Mengwei Guo and has published in prestigious journals such as IEEE Access, IEEE Transactions on Industrial Informatics and Inverse Problems.

In The Last Decade

Cheng Xing

17 papers receiving 520 citations

Hit Papers

An Intrusion Detection Model Based on Feature Reduction a... 2019 2026 2021 2023 2019 50 100 150 200

Peers

Cheng Xing
Comparison fields: 5 of 82
  • Artificial Intelligence 310
  • Computer Networks and Communications 232
  • Signal Processing 115
  • Computer Vision and Pattern Recognition 105
  • Control and Systems Engineering 76
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Hamza Kheddar Algeria View profile →
Citations per field, relative to Cheng Xing
Cheng Xing · 1×
Citations per year, relative to Cheng Xing
Cheng Xing · 1×

Countries citing papers authored by Cheng Xing

Since Specialization
Citations

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

Fields of papers citing papers by Cheng Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheng Xing

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Xing. A scholar is included among the top collaborators of Cheng Xing 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 Cheng Xing. Cheng Xing is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
# Work Indexed citations
1 1
2 1
3 3
4 1
5 12
6 8
7 128
8 8
9 29
10 1
11 58
12 22
13 14
14 8
15
An Intrusion Detection Model Based on Feature Reduction and Convolutional Neural Networks breakdown →
247
16 2
17 3

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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