Decision-making in sustainable energy transition in Southeastern Europe: probabilistic network-based model
Apstrakt
Background Sustainable energy transition of a country is complex and long-term process, which requires decision-making in all stages and at all levels, including a large number of different factors, with different causality. The main objective of this paper is the development of a probabilistic model for decision-making in sustainable energy transition in developing countries of SE Europe. The model will be developed according to the specificities of the countries for which it is intended-SE Europe. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding. Methods Research was done by using content analysis, artificial intelligence methods, software development method and test...ing. The model was developed by using MSBNx-Microsoft Research's Bayesian Network Authoring and Evaluation Tool. Results Due to the large number of insufficiently clear, but interdependent factors, the model is developed on the principle of probabilistic (Bayesian) networks of factors of interest. The paper presents the first model for supporting decision-making in the field of energy sustainability for the region of Southeastern Europe, which is based on the application of Bayesian Networks. Conclusion Testing of the developed model showed certain characteristics, discussed in paper. The application of developed model will make it possible to predict the short-term and long-term consequences that may occur during energy transition by varying these factors. Recommendations are given for further development of the model, based on Bayesian networks.
Ključne reči:
Sustainable energy transition / SE Europe / Decision-making / Bayesian networksIzvor:
Energy Sustainability and Society, 2021, 11, 1Izdavač:
- BMC, LONDON
Finansiranje / projekti:
- Nove informacione tehnologije za analitičko odlučivanje bazirane na organizaciji eksperimenta i opservaciji i njihova primena u biološkim, ekonomskim i sociološkim sistemima (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-44007)
- Slovenian Research Agency [P5-0018]
DOI: 10.1186/s13705-021-00315-3
ISSN: 2192-0567
WoS: 000712823200001
Scopus: 2-s2.0-85118233661
Institucija/grupa
Fakultet poslovne ekonomijeTY - JOUR AU - Hribar, Nena AU - Simić, Goran AU - Vukadinović, Simonida AU - Sprajc, Polona PY - 2021 UR - https://redun.educons.edu.rs/handle/123456789/429 AB - Background Sustainable energy transition of a country is complex and long-term process, which requires decision-making in all stages and at all levels, including a large number of different factors, with different causality. The main objective of this paper is the development of a probabilistic model for decision-making in sustainable energy transition in developing countries of SE Europe. The model will be developed according to the specificities of the countries for which it is intended-SE Europe. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding. Methods Research was done by using content analysis, artificial intelligence methods, software development method and testing. The model was developed by using MSBNx-Microsoft Research's Bayesian Network Authoring and Evaluation Tool. Results Due to the large number of insufficiently clear, but interdependent factors, the model is developed on the principle of probabilistic (Bayesian) networks of factors of interest. The paper presents the first model for supporting decision-making in the field of energy sustainability for the region of Southeastern Europe, which is based on the application of Bayesian Networks. Conclusion Testing of the developed model showed certain characteristics, discussed in paper. The application of developed model will make it possible to predict the short-term and long-term consequences that may occur during energy transition by varying these factors. Recommendations are given for further development of the model, based on Bayesian networks. PB - BMC, LONDON T2 - Energy Sustainability and Society T1 - Decision-making in sustainable energy transition in Southeastern Europe: probabilistic network-based model IS - 1 VL - 11 DO - 10.1186/s13705-021-00315-3 UR - conv_1096 ER -
@article{ author = "Hribar, Nena and Simić, Goran and Vukadinović, Simonida and Sprajc, Polona", year = "2021", abstract = "Background Sustainable energy transition of a country is complex and long-term process, which requires decision-making in all stages and at all levels, including a large number of different factors, with different causality. The main objective of this paper is the development of a probabilistic model for decision-making in sustainable energy transition in developing countries of SE Europe. The model will be developed according to the specificities of the countries for which it is intended-SE Europe. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding. Methods Research was done by using content analysis, artificial intelligence methods, software development method and testing. The model was developed by using MSBNx-Microsoft Research's Bayesian Network Authoring and Evaluation Tool. Results Due to the large number of insufficiently clear, but interdependent factors, the model is developed on the principle of probabilistic (Bayesian) networks of factors of interest. The paper presents the first model for supporting decision-making in the field of energy sustainability for the region of Southeastern Europe, which is based on the application of Bayesian Networks. Conclusion Testing of the developed model showed certain characteristics, discussed in paper. The application of developed model will make it possible to predict the short-term and long-term consequences that may occur during energy transition by varying these factors. Recommendations are given for further development of the model, based on Bayesian networks.", publisher = "BMC, LONDON", journal = "Energy Sustainability and Society", title = "Decision-making in sustainable energy transition in Southeastern Europe: probabilistic network-based model", number = "1", volume = "11", doi = "10.1186/s13705-021-00315-3", url = "conv_1096" }
Hribar, N., Simić, G., Vukadinović, S.,& Sprajc, P.. (2021). Decision-making in sustainable energy transition in Southeastern Europe: probabilistic network-based model. in Energy Sustainability and Society BMC, LONDON., 11(1). https://doi.org/10.1186/s13705-021-00315-3 conv_1096
Hribar N, Simić G, Vukadinović S, Sprajc P. Decision-making in sustainable energy transition in Southeastern Europe: probabilistic network-based model. in Energy Sustainability and Society. 2021;11(1). doi:10.1186/s13705-021-00315-3 conv_1096 .
Hribar, Nena, Simić, Goran, Vukadinović, Simonida, Sprajc, Polona, "Decision-making in sustainable energy transition in Southeastern Europe: probabilistic network-based model" in Energy Sustainability and Society, 11, no. 1 (2021), https://doi.org/10.1186/s13705-021-00315-3 ., conv_1096 .