References
- Deng, K., Peng, H., Dirkes, S., Gottschalk, J., Ünlübayir, C. Thul, A., Löwenstein, L. Pischinger, S. & Hameyer, K. (2021) An adaptive PMP-based model predictive energy management strategy for fuel cell hybrid railway vehicles, eTransportation, https://doi.org/10.1016/j.etran.2020.100094
- Ćalić, J., Šelmić, M., Macura, D. & Nikolić, M. (2019) Fuzzy logic application in green transport prediction of freight train energy consumption. In: Vidović, M. & Zečević, S. (Eds.) 4th Logistics International Conference (LOGIC), Belgrade, (pp. 35–44), Faculty of Traffic and Transport Engineering
- Fernández, P.M., Román, C.G. & Franco, R.I. (2016) Modelling Electric Trains Energy Consumption Using Neural Networks, Transportation Research Procedia, https://doi.org/10.1016/j.trpro.2016.12.008
- Jia, S., Peng, H., Liu, S. & Zhang X. (2009) Review of Transportation and Energy Consumption Related Research, Journal of Transportation Systems Engineering and Information Technology, https://doi.org/10.1016/S1570-6672(08)60061-6
- Jozi, A., Pinto, T., Praça, I., Ramos, S., Vale, Z., Goujon, B. & Petrisor, T. (2017) Energy consumption forecasting using neuro-fuzzy inference systems: Thales TRT building case study, In: Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI), https://doi.org/10.1109/SSCI.2017.8285200
- Liu, J. (2018) Calculation and analysis of energy consumption of Chinese national rail transport, International Journal of Energy Sector Management, https://doi.org/10.1108/IJESM-05-2016-0006
- Nikolić, M., Šelmić, M., Macura, D. & Ćalić, J. (2020) Bee Colony Optimization metaheuristic for fuzzy membership functions tuning, Expert Systems with Applications, https://doi.org/10.1016/j.eswa.2020.113601
- Pineda-Jaramillo, J., Martínez-Fernández, P., Villalba-Sanchis, I., Salvador-Zuriaga, P. & Insa-Franco, R. (2021) Predicting the traction power of metropolitan railway lines using different machine learning models, International Journal of Rail Transportation, https://doi.org/10.1080/23248378.2020.1829513
- Tang, Z., Yin, H., Yang, C., Yu, J. & Guo, H. (2021) Predicting the electricity consumption of urban rail transit based on binary nonlinear fitting regression and support vector regression, Sustainable Cities and Society, https://doi.org/10.1016/j.scs.2020.102690
- Taylan, O. & Demirbas, A. (2016) Forecasting and analysis of energy consumption for transportation in the Kingdom of Saudi Arabia, Energy Sources, Part B: Economics, Planning, and Policy, https://doi.org/10.1080/15567249.2015.1004383
- Teodorović, D. & Nikolić, M. (2020) Quantitative Methods in Transportation, CRC Press, Taylor & Francis Group, Boca Raton
- Wang, J. & Rakha, H. (2017) Electric train energy consumption modelling, Applied Energy, https://doi.org/10.1016/j.apenergy.2017.02.058
- Yang, X., Yuan, J., Yuan, J. & Mao, H. (2010) An improved WM method based on PSO for electric load forecasting, Expert Systems with Applications, https://doi.org/10.1016/j.eswa.2010.05.085