Cheng Feng

2.0k citations
37 papers · 1.0k indexed · h-index 11
Topics
Anomaly Detection Techniques and Applications (4 papers)Network Security and Intrusion Detection (3 papers)Time Series Analysis and Forecasting (3 papers)
Journals
SHILAP Revista de lepidopterologíaAdvanced Functional MaterialsSensors

In The Last Decade

Cheng Feng

30 papers receiving 939 citations

Peers

Cheng Feng
Comparison fields: 5 of 96
  • Artificial Intelligence 580
  • Computer Networks and Communications 225
  • Control and Systems Engineering 184
  • Information Systems 167
  • Computational Theory and Mathematics 136
Replace Ye Chen with:
Ye Chen China
Luiza de Macedo Mourelle Brazil
Alan Tickle Australia
Mieczyslaw M. Kokar United States
Antonio González Spain
Mohammad Abdollahi Azgomi Iran
Zied Elouedi Tunisia
Brad L. Miller United States
Claudia Linnhoff‐Popien Germany
Kagan Tumer United States
Cheng Feng relative to Ye Chen China Ye Chen's profile →
Citations per field
00.5×3.1×
Ye Chen · 1×
Citations per year

Countries citing papers authored by Cheng Feng

Since Specialization
Citations

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

Fields of papers citing papers by Cheng Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheng Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Feng. A scholar is included among the top collaborators of Cheng Feng 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 Feng. Cheng Feng 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
1 1
2 4
3 1
4 0
5 1
6 3
7 1
8 3
9 2
10 5
11 68
12 7
13 2
14 4
15 9
16 0
17 69
18 13
19 3
20
Efficient Induction of Logic Programs
318

About Cheng Feng

Cheng Feng is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 37 papers that have together received 1.0k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), Network Security and Intrusion Detection (3 papers) and Time Series Analysis and Forecasting (3 papers). The work is most often cited by research in Artificial Intelligence (580 citations), Signal Processing (110 citations) and Computer Networks and Communications (225 citations). Cheng Feng has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Stephen Muggleton, Ross D. King, A. Sutherland, Deeph Chana, Tingting Li, Venkata Reddy Palleti, Aditya P. Mathur, Xinyu Shao, Jane Hillston and Bin Dong. Their work appears in journals such as SHILAP Revista de lepidopterología, Advanced Functional Materials and Sensors.

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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