Eva Volná
Impact in
-
- Digital Transformation in Industry
Papers in
-
- Neural Networks and Applications 13
- Fuzzy Logic and Control Systems 8
- Advanced Computational Techniques and Applications 4
- Metaheuristic Optimization Algorithms Research 4
- Evolutionary Algorithms and Applications 3
- Cognitive Computing and Networks 2
- Co-authors
- Martin Kotyrba (36 shared papers)Petr Bujok (1 shared paper)Roman Maršálek (1 shared paper)Zuzana Komínková Oplatková (4 shared papers)Ivan Zelinka (1 shared paper)Roman Šenkeřík (2 shared papers)Petr Kulišťák (1 shared paper)Michal Bar (1 shared paper)
- Journals
- Neural Networks (2 papers)Applied Sciences (2 papers)Applied Mathematics and Computation (2 papers)Swarm and Evolutionary Computation (1 paper)BMC Medical Informatics and Decision Making (1 paper)
- Partner nations
- Czechia
In The Last Decade
Eva Volná
38 papers receiving 237 citations
Peers
Comparison fields: 5 of 84
- Medical Laboratory Technology 5
- Industrial and Manufacturing Engineering 29
- Computer Vision and Pattern Recognition 49
- Artificial Intelligence 76
- Management Science and Operations Research 24
Countries citing papers authored by Eva Volná
This map shows the geographic impact of Eva Volná'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 Eva Volná with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva Volná more than expected).
Fields of papers citing papers by Eva Volná
This network shows the impact of papers produced by Eva Volná. 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 Eva Volná. The network helps show where Eva Volná may publish in the future.
Co-authors
The 8 scholars most cited alongside Eva Volná, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 34 | |
| 2 | 2021 | 25 | |
| 3 | 2021 | 19 | |
| 4 | 2021 | 18 | |
| 5 | 2015 | 18 | |
| 6 | 2013 | 12 | |
| 7 | 2019 | 11 | |
| 8 | 2022 | 11 | |
| 9 | 2018 | 10 | |
| 10 | 2014 | 9 | |
| 11 | 2015 | 8 | |
| 12 | 2021 | 7 | |
| 13 | 2017 | 6 | |
| 14 | 2015 | 5 | |
| 15 | 2023 | 5 | |
| 16 | 2017 | 5 | |
| 17 | 2021 | 5 | |
| 18 | 2014 | 5 | |
| 19 | 2023 | 3 | |
| 20 | 2013 | 3 |
About Eva Volná
Eva Volná is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 45 papers that have together received 251 indexed citations. Recurring topics across this work include Neural Networks and Applications (13 papers), Fuzzy Logic and Control Systems (8 papers), Advanced Computational Techniques and Applications (4 papers), Metaheuristic Optimization Algorithms Research (4 papers), Scheduling and Optimization Algorithms (3 papers), Modeling, Simulation, and Optimization (3 papers), Evolutionary Algorithms and Applications (3 papers) and Cognitive Computing and Networks (2 papers). The work is most often cited by research in Medical Laboratory Technology (5 citations), Industrial and Manufacturing Engineering (29 citations), Computer Vision and Pattern Recognition (49 citations), Artificial Intelligence (76 citations) and Management Science and Operations Research (24 citations). Eva Volná has collaborated with scholars based in Czechia. Frequent co-authors include Martin Kotyrba, Petr Bujok, Roman Maršálek, Zuzana Komínková Oplatková, Ivan Zelinka, Roman Šenkeřík, Petr Kulišťák and Michal Bar. Their work appears in journals such as Neural Networks, Applied Sciences, Applied Mathematics and Computation, Swarm and Evolutionary Computation and BMC Medical Informatics and Decision Making.
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.