Ivan Zelinka

6.1k citations
235 papers · 2.7k · h-index 26

Impact in

Papers in

Ivan Zelinka

221 papers receiving 2.6k citations

Peers

Ivan Zelinka
Comparison fields: 5 of 130
  • Artificial Intelligence 1.4k
  • Statistical and Nonlinear Physics 486
  • Signal Processing 359
  • Computer Networks and Communications 568
  • Computational Theory and Mathematics 358
Replace Tinghuai Ma with:
Tinghuai Ma China
Rob A. Rutenbar United States
Mohammad Reza Meybodi Iran
Geoffrey J. Gordon United States
Deyun Zhou China
Qingsheng Zhu China
Mehrdad Mahdavi United States
Feng Zou China
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Citations per field
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Citations per year

Countries citing papers authored by Ivan Zelinka

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Zelinka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 235 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020136
2 2012126
3
Mechanical engineering design optimization by differential evolution
199988
4 201082
5 201278
6 202074
7 201368
8 201566
9 202063
10 201059
11 201858
12
MIXED INTEGER-DISCRETE-CONTINUOUS OPTIMIZATION BY DIFFERENTIAL EVOLUTION Part 1: the optimization method
200455
13 201652
14 202250
15 202149
16 202046
17 201138
18 200535
19 200735
20 202234

About Ivan Zelinka

Ivan Zelinka is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Computer Networks and Communications and Control and Systems Engineering, having authored 235 papers that have together received 2.7k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (54 papers), Evolutionary Algorithms and Applications (51 papers), Neural Networks and Applications (43 papers), Chaos control and synchronization (41 papers), Complex Network Analysis Techniques (16 papers), Chaos-based Image/Signal Encryption (15 papers), Complex Systems and Time Series Analysis (14 papers) and Modeling, Simulation, and Optimization (12 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Statistical and Nonlinear Physics (486 citations), Signal Processing (359 citations), Computer Networks and Communications (568 citations) and Computational Theory and Mathematics (358 citations). Ivan Zelinka has collaborated with scholars based in Czechia, Vietnam and India. Frequent co-authors include Roman Šenkeřík, Donald Davendra, Eslam Amer, Ajith Abraham, Jouni Lampinen, Swagatam Das, Václav Snåšel, Michal Pluháček, Zuzana Komínková Oplatková and Thanh Cong Truong. Their work appears in journals such as Swarm and Evolutionary Computation, Computers & Mathematics with Applications, Soft Computing, Engineering Applications of Artificial Intelligence and Mathematical and Computer Modelling.

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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