Michal Holčapek

851 citations
60 papers · 457 · h-index 12

Impact in

Papers in

Michal Holčapek

55 papers receiving 430 citations

Peers

Michal Holčapek
Comparison fields: 5 of 47
  • Management Science and Operations Research 223
  • Computational Theory and Mathematics 270
  • Statistics and Probability 125
  • Artificial Intelligence 237
  • Signal Processing 44
Replace Martina Daňková with:
Martina Daňková Czechia
Mikel Sesma‐Sara Spain
Maurice Frank Guatemala
N. O. Alshehri Saudi Arabia
Anestis G. Hatzimichailidis Greece
Junsheng Qiao China
Lingqiang Li China
Qiu Jin China
Chun Yong Wang China
Andrea Stupňanová Slovakia
Michal Holčapek relative to Martina Daňková Czechia Martina Daňková's profile →
Citations per field
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Martina Daňková · 1×
Citations per year

Countries citing papers authored by Michal Holčapek

Since Specialization
Citations

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

Fields of papers citing papers by Michal Holčapek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Michal Holčapek, 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 Michal Holčapek Line = papers co-authored together Michal Holčapek links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201941
2 201441
3 200931
4 201128
5 201426
6 201523
7 200822
8 201117
9 201416
10 201714
11 201613
12 201211
13 201210
14 201710
15 20149
16 20138
17 20158
18 20217
19
A probability density function estimation using F-transform
20107
20 20157

About Michal Holčapek

Michal Holčapek is a scholar working on Computational Theory and Mathematics, Management Science and Operations Research, Artificial Intelligence, Statistics and Probability and Economics and Econometrics, having authored 60 papers that have together received 457 indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (32 papers), Rough Sets and Fuzzy Logic (31 papers), Advanced Algebra and Logic (29 papers), Fuzzy Systems and Optimization (23 papers), Multi-Criteria Decision Making (19 papers), Fuzzy and Soft Set Theory (19 papers), Complex Systems and Time Series Analysis (3 papers) and Advanced Computational Techniques in Science and Engineering (2 papers). The work is most often cited by research in Management Science and Operations Research (223 citations), Computational Theory and Mathematics (270 citations), Statistics and Probability (125 citations), Artificial Intelligence (237 citations) and Signal Processing (44 citations). Michal Holčapek has collaborated with scholars based in Czechia, United States and Slovakia. Frequent co-authors include Antonı́n Dvořák, Tomáš Tichý, Irina Perfilieva, Martin Štěpnička, Владик Крейнович, Vilém Novák, Jiří Močkoř, Jan Paseka, Roman Farana and Joseph Hamill. Their work appears in journals such as Fuzzy Sets and Systems, Information Sciences, Soft Computing, Logic Journal of IGPL and Kybernetika.

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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