N. Boonsatit

512 citations
23 papers · 373 · h-index 10

Impact in

Papers in

N. Boonsatit

23 papers receiving 355 citations

Peers

N. Boonsatit
Comparison fields: 5 of 51
  • Computer Networks and Communications 179
  • Statistical and Nonlinear Physics 72
  • Modeling and Simulation 24
  • Control and Systems Engineering 93
  • Artificial Intelligence 97
Replace Seyed Mehdi Abedi Pahnehkolaei with:
Seyed Mehdi Abedi Pahnehkolaei Iran
Guo Huang China
Guoqiang Tan China
Farouk Zouari Tunisia
Jason Sheng-Hong Tsai Taiwan
S. K. Korovin Russia
Henryk Mikołaj Górecki Poland
Mohammad Ali Nekoui Iran
Baoli Ma China
N. Boonsatit relative to Seyed Mehdi Abedi Pahnehkolaei Iran Seyed Mehdi Abedi Pahnehkolaei's profile →
Citations per field
00.5×1.6×
Seyed Mehdi Abedi Pahnehkolaei · 1×
Citations per year

Countries citing papers authored by N. Boonsatit

Since Specialization
Citations

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

Fields of papers citing papers by N. Boonsatit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202168
2 202147
3 202146
4 202245
5 202131
6 201627
7 202120
8 202119
9 202212
10 202211
11 20219
12 20216
13 20225
14 20224
15 20224
16 20213
17 20223
18 20223
19 20233
20 20223

About N. Boonsatit

N. Boonsatit is a scholar working on Computer Networks and Communications, Control and Systems Engineering, Electrical and Electronic Engineering, Computational Mechanics and Management Science and Operations Research, having authored 23 papers that have together received 373 indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (10 papers), Nonlinear Dynamics and Pattern Formation (5 papers), Nanofluid Flow and Heat Transfer (4 papers), Multi-Criteria Decision Making (4 papers), Stability and Control of Uncertain Systems (3 papers), Distributed Control Multi-Agent Systems (3 papers), Fluid Dynamics and Turbulent Flows (3 papers) and Fuzzy and Soft Set Theory (3 papers). The work is most often cited by research in Computer Networks and Communications (179 citations), Statistical and Nonlinear Physics (72 citations), Modeling and Simulation (24 citations), Control and Systems Engineering (93 citations) and Artificial Intelligence (97 citations). N. Boonsatit has collaborated with scholars based in Thailand, India and Australia. Frequent co-authors include Grienggrai Rajchakit, Porpattama Hammachukiattikul, Chee Peng Lim, R. Sriraman, Praveen Agarwal, Chutiphon Pukdeboon, Anuwat Jirawattanapanit, M. Syed Ali, Umair Khan and Zehba Raizah. Their work appears in journals such as IEEE Access, Advances in Difference Equations, Complexity, Lubricants and Computer Modeling in Engineering & Sciences.

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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