Alexander E. Prosvirin

921 citations
21 papers · 673 · 1 hit paper · h-index 15

Impact in

Papers in

Alexander E. Prosvirin

21 papers receiving 648 citations

Alexander E. Prosvirin's Hit Papers

Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers 2020 · 204 citations
2040+2+4Years since publication50100150200

Peers

Alexander E. Prosvirin
Comparison fields: 5 of 79
  • Control and Systems Engineering 514
  • Medical Laboratory Technology 14
  • Mechanical Engineering 338
  • Mechanics of Materials 183
  • Industrial and Manufacturing Engineering 52
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Citations per field
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Citations per year

Countries citing papers authored by Alexander E. Prosvirin

Since Specialization
Citations

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

Fields of papers citing papers by Alexander E. Prosvirin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alexander E. Prosvirin. 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 Alexander E. Prosvirin. The network helps show where Alexander E. Prosvirin may publish in the future.

Co-authors

The 20 scholars most cited alongside Alexander E. Prosvirin, 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 Alexander E. Prosvirin Line = papers co-authored together Alexander E. Prosvirin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers
Hit paper breakdown →
2020204
2 201875
3 202175
4 202342
5 201939
6 202133
7 202124
8 202023
9 201822
10 202020
11 201918
12 201817
13 202217
14 202016
15 202015
16 202014
17 20207
18 20204
19 20173
20 20143

About Alexander E. Prosvirin

Alexander E. Prosvirin is a scholar working on Control and Systems Engineering, Mechanical Engineering, Mechanics of Materials, Surgery and Biomaterials, having authored 21 papers that have together received 673 indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (16 papers), Engineering Diagnostics and Reliability (9 papers), Gear and Bearing Dynamics Analysis (9 papers), Fault Detection and Control Systems (7 papers), Hydraulic and Pneumatic Systems (2 papers), Bone Tissue Engineering Materials (2 papers), COVID-19 diagnosis using AI (1 paper) and Bone health and osteoporosis research (1 paper). The work is most often cited by research in Control and Systems Engineering (514 citations), Medical Laboratory Technology (14 citations), Mechanical Engineering (338 citations), Mechanics of Materials (183 citations) and Industrial and Manufacturing Engineering (52 citations). Alexander E. Prosvirin has collaborated with scholars based in South Korea, Russia and Pakistan. Frequent co-authors include Jong-Myon Kim, Rafia Nishat Toma, M. M. Manjurul Islam, Farzin Piltan, Zahoor Ahmad, Cheol Hong Kim, Jae‐Young Kim, Kichang Im, Sheraz Ali Khan and Ali Rohan. Their work appears in journals such as Sensors, IEEE Access, Applied Sciences, Journal of Intelligent & Fuzzy Systems and Soft Computing.

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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