Nikola Anđelić

1.4k total citations
75 papers, 899 citations indexed

About

Nikola Anđelić is a scholar working on Artificial Intelligence, Control and Systems Engineering and Mechanical Engineering. According to data from OpenAlex, Nikola Anđelić has authored 75 papers receiving a total of 899 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 16 papers in Control and Systems Engineering and 14 papers in Mechanical Engineering. Recurrent topics in Nikola Anđelić's work include AI in cancer detection (8 papers), Network Security and Intrusion Detection (7 papers) and COVID-19 diagnosis using AI (7 papers). Nikola Anđelić is often cited by papers focused on AI in cancer detection (8 papers), Network Security and Intrusion Detection (7 papers) and COVID-19 diagnosis using AI (7 papers). Nikola Anđelić collaborates with scholars based in Croatia, Serbia and Slovakia. Nikola Anđelić's co-authors include Ivan Lorencin, Zlatan Car, Vedran Mrzljak, Sandi Baressi Šegota, Josip Španjol, Milan Sága, Tomislav Ćabov, Tijana Šušteršič, Nenad Filipović and Paolo Blecich and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Energy and Sensors.

In The Last Decade

Nikola Anđelić

67 papers receiving 859 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nikola Anđelić Croatia 16 203 200 166 155 128 75 899
Ivan Lorencin Croatia 16 186 0.9× 197 1.0× 176 1.1× 146 0.9× 115 0.9× 73 878
Zlatan Car Croatia 18 251 1.2× 234 1.2× 180 1.1× 170 1.1× 135 1.1× 100 1.1k
Sandi Baressi Šegota Croatia 13 102 0.5× 127 0.6× 141 0.8× 118 0.8× 57 0.4× 64 636
Imre Felde Hungary 16 388 1.9× 161 0.8× 139 0.8× 53 0.3× 53 0.4× 100 936
Om Prakash Verma India 17 104 0.5× 209 1.0× 44 0.3× 187 1.2× 118 0.9× 73 931
Vedran Mrzljak Croatia 19 500 2.5× 110 0.6× 85 0.5× 158 1.0× 228 1.8× 92 1.1k
Hongping Hu China 18 58 0.3× 278 1.4× 96 0.6× 162 1.0× 132 1.0× 56 934
Muhammad Muneeb Pakistan 11 44 0.2× 381 1.9× 143 0.9× 72 0.5× 425 3.3× 30 1.2k
Sanjoy Chakraborty India 23 67 0.3× 565 2.8× 35 0.2× 115 0.7× 123 1.0× 33 1.3k
Muzhou Hou China 17 46 0.2× 430 2.1× 155 0.9× 91 0.6× 155 1.2× 83 1.1k

Countries citing papers authored by Nikola Anđelić

Since Specialization
Citations

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

Fields of papers citing papers by Nikola Anđelić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nikola Anđelić

This figure shows the co-authorship network connecting the top 25 collaborators of Nikola Anđelić. A scholar is included among the top collaborators of Nikola Anđelić based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nikola Anđelić. Nikola Anđelić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Anđelić, Nikola, Sandi Baressi Šegota, & Vedran Mrzljak. (2025). Application of Symbolic Classifiers and Multi-Ensemble Threshold Techniques for Android Malware Detection. Big Data and Cognitive Computing. 9(2). 27–27.
2.
Anđelić, Nikola & Sandi Baressi Šegota. (2024). Enhancing Network Intrusion Detection: A Genetic Programming Symbolic Classifier Approach. Information. 15(3). 154–154. 1 indexed citations
3.
Anđelić, Nikola, Ivan Lorencin, Vedran Mrzljak, & Zlatan Car. (2024). On the application of symbolic regression in the energy sector: Estimation of combined cycle power plant electrical power output using genetic programming algorithm. Engineering Applications of Artificial Intelligence. 133. 108213–108213. 10 indexed citations
4.
Šegota, Sandi Baressi, Vedran Mrzljak, Nikola Anđelić, Igor Poljak, & Zlatan Car. (2023). Use of Synthetic Data in Maritime Applications for the Problem of Steam Turbine Exergy Analysis. Journal of Marine Science and Engineering. 11(8). 1595–1595. 3 indexed citations
5.
Anđelić, Nikola, et al.. (2023). Drive System Inverter Modeling Using Symbolic Regression. Electronics. 12(3). 638–638. 1 indexed citations
6.
7.
Anđelić, Nikola, et al.. (2023). Cervical Cancer Diagnostics Using Machine Learning Algorithms and Class Balancing Techniques. Applied Sciences. 13(2). 1061–1061. 23 indexed citations
8.
Anđelić, Nikola, et al.. (2022). Detection of Malicious Websites Using Symbolic Classifier. Future Internet. 14(12). 358–358. 3 indexed citations
9.
Anđelić, Nikola, et al.. (2022). Estimation of Excitation Current of a Synchronous Machine Using Machine Learning Methods. Computers. 12(1). 1–1. 4 indexed citations
10.
Šegota, Sandi Baressi, et al.. (2022). Automated Detection and Classification of Returnable Packaging Based on YOLOV4 Algorithm. Applied Sciences. 12(21). 11131–11131. 6 indexed citations
11.
12.
Anđelić, Nikola, Sandi Baressi Šegota, Ivan Lorencin, & Zlatan Car. (2022). The Development of Symbolic Expressions for Fire Detection with Symbolic Classifier Using Sensor Fusion Data. Sensors. 23(1). 169–169. 9 indexed citations
13.
Anđelić, Nikola, Sandi Baressi Šegota, Ivan Lorencin, et al.. (2021). Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm. International Journal of Environmental Research and Public Health. 18(3). 959–959. 12 indexed citations
14.
Anđelić, Nikola, Sandi Baressi Šegota, Ivan Lorencin, et al.. (2021). Use of Genetic Programming for the Estimation of CODLAG Propulsion System Parameters. Journal of Marine Science and Engineering. 9(6). 612–612. 7 indexed citations
15.
Šušteršič, Tijana, Ivan Lorencin, Sandi Baressi Šegota, et al.. (2021). Artificial intelligence approach towards assessment of condition of COVID-19 patients - Identification of predictive biomarkers associated with severity of clinical condition and disease progression. Computers in Biology and Medicine. 138. 104869–104869. 5 indexed citations
16.
Šegota, Sandi Baressi, Ivan Lorencin, Nikola Anđelić, et al.. (2021). Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review. International Journal of Environmental Research and Public Health. 18(8). 4287–4287. 34 indexed citations
17.
Šegota, Sandi Baressi, Ivan Lorencin, Nikola Anđelić, et al.. (2021). Semantic Segmentation of Urinary Bladder Cancer Masses from CT Images: A Transfer Learning Approach. Biology. 10(11). 1134–1134. 10 indexed citations
18.
Lorencin, Ivan, Sandi Baressi Šegota, Nikola Anđelić, et al.. (2021). On Urinary Bladder Cancer Diagnosis: Utilization of Deep Convolutional Generative Adversarial Networks for Data Augmentation. Biology. 10(3). 175–175. 17 indexed citations
19.
Anđelić, Nikola, Zlatan Car, & Marko Čanađija. (2019). NEMS Resonators for Detection of Chemical Warfare Agents Based on Graphene Sheet. Mathematical Problems in Engineering. 2019(1). 9 indexed citations
20.
Mrzljak, Vedran, Paolo Blecich, Nikola Anđelić, & Ivan Lorencin. (2019). Energy and Exergy Analyses of Forced Draft Fan for Marine Steam Propulsion System during Load Change. Journal of Marine Science and Engineering. 7(11). 381–381. 26 indexed citations

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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