| Author(s) | Title | Issue Date | Appears in | Rank |
| Janković, Radmila ; Mihajlović, Ivan | Development and implementation of the numerical model for predicting the values of the ecological footprint, based on the Monte Carlo methodology | 2018 | FIKUSZ Symposium for Young Researchers; 189-200 | M30 |
| Petkovski, Ivana ; Mihajlović, Ivan; Fedajev, Aleksandra | Hybrid CRITIC-TOPSIS model for prioritizing digitally developed countries in the light of energy indicators | 2022 | XVII International May Conference on Strategic Management – IMCSM22 May 28, 2022, Bor, Serbia; IMCSM Proceedings; 264-277 | M33 |
| Mihajlović, Ivan; Dimitrievska, Dragana; Veličkovska, Ivana | Logistic process indicator (LPI) as the measure of infrastructural and regional development | 2020 | XV FIKUSZ 2020 International Conference - Symposium for young researchers; 5-23 | M33 |
| Janković, Radmila ; Mihajlović, Ivan; Štrbac, Nada; Amelio, Alessia | Machine learning models for ecological footprint prediction based on energy parameters | 17-Nov-2020 | Neural Computing and Applications | M21 |
| Janković, Radmila ; Mihajlović, Ivan; Štrbac, Nada | Modeling the influence of the energy sources and consumption on the resulting ecological footprint | 2019 | YOUng ResearcherS Conference (YOURS) 2019, 26-27 March, Belgrade, Serbia; 23 | M64 |
| Janković, Radmila ; Mihajlović, Ivan; Amelio, Alessia; Draganov, Ivo R. | Predicting the Ecological Footprint: A Case Study for Italy, Pakistan and China | 28-Jul-2021 | 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies, ICEST 2021, Sozopol, 16 June 2021 - 18 June 2021; 9483528 | M33 |
| Veličkovska, Ivana ; Mihajlović, Ivan; Njagulović, Boban | Prediction of the copper production in the framework of electrical energy consumption using artificial neural network | 2020 | International May Conference on Strategic Management – IMCSM20 September 25-27, 2020, Bor, Serbia; 411-423 | M33 |
| Janković, Radmila ; Mihajlović, Ivan; Amelio, Alessia | Time Series Vector Autoregression Prediction of the Ecological Footprint based on Energy Parameters | 2019 | 5th Jubilee Virtual International Conference on Science Technology and Management in Energy, Niš, October 28-29, 2019; 55-62 | M33 |
