Miodrag Živković
- Artificial Intelligence top 0.5%
- Anomaly Detection Techniques and Applications 22
- Metaheuristic Optimization Algorithms Research 17
- Neural Networks and Applications 15
- Machine Learning and ELM 15
- Solar Radiation and Photovoltaics 13
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- Network Security and Intrusion Detection 19
- Information Systems top 1%
- Signal Processing top 5%
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- Stock Market Forecasting Methods 11
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- Energy Load and Power Forecasting 18
Miodrag Živković
166 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Artificial Intelligence 1.5k
- Computer Networks and Communications 647
- Information Systems 535
- Signal Processing 246
- Management Science and Operations Research 276
Countries citing papers authored by Miodrag Živković
This map shows the geographic impact of Miodrag Živković'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 Miodrag Živković with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miodrag Živković more than expected).
Fields of papers citing papers by Miodrag Živković
This network shows the impact of papers produced by Miodrag Živković. 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 Miodrag Živković. The network helps show where Miodrag Živković may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Miodrag Živković, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 3 | |
| 2 | 2025 | 8 | |
| 3 | Two-tier deep and machine learning approach optimized by adaptive multi-population firefly algorithm for software defects predictionbreakdown → | 2025 | 22 |
| 4 | 2025 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 18 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2023 | 36 | |
| 15 | 2023 | 22 | |
| 16 | 2023 | 3 | |
| 17 | 2023 | 20 | |
| 18 | 2023 | 86 | |
| 19 | 2022 | 34 | |
| 20 | 2021 | 29 |
About Miodrag Živković
Miodrag Živković is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems, having authored 182 papers that have together received 3.3k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (22 papers), Network Security and Intrusion Detection (19 papers), Energy Load and Power Forecasting (18 papers), Metaheuristic Optimization Algorithms Research (17 papers), Neural Networks and Applications (15 papers), Machine Learning and ELM (15 papers), Solar Radiation and Photovoltaics (13 papers) and Stock Market Forecasting Methods (11 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Computer Networks and Communications (647 citations) and Information Systems (535 citations). Miodrag Živković has collaborated with scholars based in Serbia, India and Taiwan. Frequent co-authors include Nebojša Bačanin, Ivana Strumberger, Miloš Antonijević, Timea Bezdan, K. Venkatachalam, Luka Jovanović, Aleksandar Petrović, Cătălin Stoean, Milan Tuba and Eva Tuba. Their work appears in journals such as The Science of The Total Environment, Scientific Reports and IEEE Access.
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.