Forecasting of Greenhouse Gas Emissions in Serbia Using Artificial Neural Networks
Abstract
Serbia is attempting to synchronize its development with the basic assumptions of sustainable development and, consequently, data about environmental impact are necessary. The main goal of this study was to investigate and evaluate the possibility of using the artificial neural network technique for predicting the environmental indicators of sustainable development, in order to overcome the problem of incomplete data and to simulate various development scenarios and their environmental impact. Based on the results obtained, it may be concluded that an artificial neural network can be applied to model the greenhouse gas emissions as one of the environmental parameters of sustainable development.
Keywords:
energy consumption / neural network / pressure indicators / Serbia / sustainable developmentSource:
Energy Sources Part A-Recovery Utilization and Environmental Effects, 2013, 35, 8, 733-740Publisher:
- Taylor & Francis Inc, Philadelphia
Funding / projects:
DOI: 10.1080/15567036.2010.514597
ISSN: 1556-7036
WoS: 000322302500005
Scopus: 2-s2.0-84874454647
Institution/Community
Tehnološko-metalurški fakultetTY - JOUR AU - Radojević, D. AU - Pocajt, Viktor AU - Popović, Ivanka AU - Perić-Grujić, Aleksandra AU - Ristić, M. PY - 2013 UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/2418 AB - Serbia is attempting to synchronize its development with the basic assumptions of sustainable development and, consequently, data about environmental impact are necessary. The main goal of this study was to investigate and evaluate the possibility of using the artificial neural network technique for predicting the environmental indicators of sustainable development, in order to overcome the problem of incomplete data and to simulate various development scenarios and their environmental impact. Based on the results obtained, it may be concluded that an artificial neural network can be applied to model the greenhouse gas emissions as one of the environmental parameters of sustainable development. PB - Taylor & Francis Inc, Philadelphia T2 - Energy Sources Part A-Recovery Utilization and Environmental Effects T1 - Forecasting of Greenhouse Gas Emissions in Serbia Using Artificial Neural Networks EP - 740 IS - 8 SP - 733 VL - 35 DO - 10.1080/15567036.2010.514597 ER -
@article{ author = "Radojević, D. and Pocajt, Viktor and Popović, Ivanka and Perić-Grujić, Aleksandra and Ristić, M.", year = "2013", abstract = "Serbia is attempting to synchronize its development with the basic assumptions of sustainable development and, consequently, data about environmental impact are necessary. The main goal of this study was to investigate and evaluate the possibility of using the artificial neural network technique for predicting the environmental indicators of sustainable development, in order to overcome the problem of incomplete data and to simulate various development scenarios and their environmental impact. Based on the results obtained, it may be concluded that an artificial neural network can be applied to model the greenhouse gas emissions as one of the environmental parameters of sustainable development.", publisher = "Taylor & Francis Inc, Philadelphia", journal = "Energy Sources Part A-Recovery Utilization and Environmental Effects", title = "Forecasting of Greenhouse Gas Emissions in Serbia Using Artificial Neural Networks", pages = "740-733", number = "8", volume = "35", doi = "10.1080/15567036.2010.514597" }
Radojević, D., Pocajt, V., Popović, I., Perić-Grujić, A.,& Ristić, M.. (2013). Forecasting of Greenhouse Gas Emissions in Serbia Using Artificial Neural Networks. in Energy Sources Part A-Recovery Utilization and Environmental Effects Taylor & Francis Inc, Philadelphia., 35(8), 733-740. https://doi.org/10.1080/15567036.2010.514597
Radojević D, Pocajt V, Popović I, Perić-Grujić A, Ristić M. Forecasting of Greenhouse Gas Emissions in Serbia Using Artificial Neural Networks. in Energy Sources Part A-Recovery Utilization and Environmental Effects. 2013;35(8):733-740. doi:10.1080/15567036.2010.514597 .
Radojević, D., Pocajt, Viktor, Popović, Ivanka, Perić-Grujić, Aleksandra, Ristić, M., "Forecasting of Greenhouse Gas Emissions in Serbia Using Artificial Neural Networks" in Energy Sources Part A-Recovery Utilization and Environmental Effects, 35, no. 8 (2013):733-740, https://doi.org/10.1080/15567036.2010.514597 . .