Rafig Agaev

475 citations
19 papers · 238 · h-index 7

Impact in

Papers in

Rafig Agaev

14 papers receiving 232 citations

Peers

Rafig Agaev
Comparison fields: 5 of 59
  • Computer Networks and Communications 144
  • Statistical and Nonlinear Physics 65
  • Geometry and Topology 30
  • General Decision Sciences 6
  • Computational Theory and Mathematics 42
Replace Kenneth A. Berman with:
Kenneth A. Berman United States
Mehmet E. Yildiz United States
Damon Mosk-Aoyama United States
Dieter Mitsche France
Bernd S. W. Schröder United States
Haibin Shao China
George B. Mertzios United Kingdom
Mengzhuo Luo China
Paolo D’Alessandro Italy
Rafig Agaev relative to Kenneth A. Berman United States Kenneth A. Berman's profile →
Citations per field
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Kenneth A. Berman · 1×
Citations per year

Countries citing papers authored by Rafig Agaev

Since Specialization
Citations

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

Fields of papers citing papers by Rafig Agaev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 2 scholars most cited alongside Rafig Agaev, 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 Rafig Agaev Line = papers co-authored together Rafig Agaev links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2004127
2 200134
3 199324
4 201111
5 20029
6 19949
7 20107
8 20055
9 20175
10 20212
11 20192
12 20231
13 20131
14 20221
15 20080
16 20210
17 20130
18 20230
19 20190

About Rafig Agaev

Rafig Agaev is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics, Computational Theory and Mathematics, Control and Systems Engineering and Geometry and Topology, having authored 19 papers that have together received 238 indexed citations. Recurring topics across this work include Distributed Control Multi-Agent Systems (9 papers), Neural Networks Stability and Synchronization (8 papers), Opinion Dynamics and Social Influence (6 papers), Matrix Theory and Algorithms (5 papers), Graph theory and applications (5 papers), Topological and Geometric Data Analysis (4 papers), Complex Network Analysis Techniques (3 papers) and Advanced Research in Systems and Signal Processing (3 papers). The work is most often cited by research in Computer Networks and Communications (144 citations), Statistical and Nonlinear Physics (65 citations), Geometry and Topology (30 citations), General Decision Sciences (6 citations) and Computational Theory and Mathematics (42 citations). Rafig Agaev has collaborated with scholars based in Russia. Frequent co-authors include Pavel Chebotarev and Fuad Aleskerov. Their work appears in journals such as Advances in Applied Mathematics, Mathematical Social Sciences, Information Sciences, Linear Algebra and its Applications and Automation and Remote Control.

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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