| Title: | Decision-making in sustainable energy transition in Southeastern Europe : probabilistic network-based model |
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| Authors: | ID Hribar, Nena (Author)
ID Šimić, Goran (Author)
ID Vukadinović, Simonida (Author)
ID Šprajc, Polona (Author) |
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| Files: |  Hribar-2021-Decision-making_in_sustainable_ene.pdf (3,93 MB)
MD5: A3363B46FAC3CBF7FA3534F5B4D80DB6
 https://doi.org/10.1186/s13705-021-00315-3
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FOV - Faculty of Organizational Sciences in Kranj
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| 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. |
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| Keywords: | sustainable energy transition, SE Europe, decision-making, Bayesian networks |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 07.09.2021 |
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| Article acceptance date: | 12.10.2021 |
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| Publication date: | 29.10.2021 |
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| Publisher: | Springer |
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| Year of publishing: | 2021 |
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| Number of pages: | Str. 1-14 |
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| Numbering: | Letn. 11, Št. članka 39 |
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| PID: | 20.500.12556/DKUM-89943  |
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| UDC: | 502.131.1:519.816 |
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| ISSN on article: | 2192-0567 |
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| COBISS.SI-ID: | 83147779 |
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| DOI: | 10.1186/s13705-021-00315-3 |
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| Publication date in DKUM: | 19.08.2024 |
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| Views: | 273 |
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| Downloads: | 17 |
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| Metadata: |    |
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| Categories: | Misc.
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