Research Article

Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model

Volume: 16 Number: 3 August 17, 2026
TR EN

Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model

Abstract

This study presents an integrated approach that combines fuzzy logic, entropy, and Directed Network Analysis (DNA) within the framework of multi-criteria decision-making (MCDM), detecting the criteria affecting hydroelectric energy production and aiming to enhance the quality and robustness of strategic decision processes. In this framework, the weights of decision criteria were determined using both subjective and objective techniques. Subjective assessments were derived from expert knowledge, experience, and perceptions, while objective weights were calculated based on data-driven mathematical methods. By integrating these two perspectives, the model ensures that the relative importance of each criterion is not solely dependent on human judgment but is also grounded in empirical evidence. Furthermore, the DNA method was employed to identify the direction and intensity of causal relationships among the criteria. To examine the robustness of the proposed model, a sensitivity analysis was performed by varying the parameter that balances the entropy-based and directed network. This method provided valuable information about the systemic structure of the decision environment, given the increasing need for sustainable and efficient energy production, by clearly showing which criteria have a dominant influence over others.

Keywords

Fuzzy Logic, Entropy, Directed Network Analysis, Hydroelectric Energy, Sustainability

References

  1. Aka, M., Kentel, E. and Kucukali, S. (2017). A fuzzy logic tool to evaluate low-head hydropower technologies at the outlet of wastewater treatment plants, Renewable and Sustainable Energy Reviews, 68(1), 727-737. Doi: https://doi.org/10.1016/j.rser.2016.10.010
  2. Akarçeşme, Y. (2019). The Importance of Hydroelectric Potential for Türkiye. Master's Thesis. Istanbul University.
  3. Alnour, M., Ali, M., Abdalla, A., Abdelrahman, R., and Khalil, H. (2022). How do urban population growth, hydropower consumption and natural resources rent shape environmental quality in Sudan, World Development Sustainability, 1, https://doi.org/10.1016/j.wds.2022.100029.
  4. Azad, A.S., Rahaman, M.S.A., Watada, J., Vasant, P., and Vintaned, J.A.G. (2020). Optimization of the hydropower energy generation using Meta-Heuristic approaches: A review. Energy Reports, 6, 2230-2248. https://doi.org/10.1016/j.egyr.2020.08.009.
  5. Barrat, A., Barthélémy, M., Pastor-Satorras, R., Vespignani, A. (2004). The architecture of complex weighted networks, Proceedings of the National Academy of Sciences, 101 (11), pp. 3747-3752
  6. Bullmore, E., and Olaf, S. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems, Nature Reviews Neuroscience, 10(3), 186-198. doi: 10.1038/nrn2575 PMID: 19190637.
  7. Candar, B. (2022). Assessment of Environmental Impacts of Hydroelectric Power Plant Projects Built in Turkey, Master's Thesis, Bursa Uludağ University, Institute of Science, Bursa.
  8. Chen, C.C. (2024). Comparative impacts of energy sources on environmental quality: A five-decade analysis of Germany’s energiewende, Energy Reports, 11, 3550-3561. https://doi.org/10.1016/j.egyr.2024.03.027.
  9. Cheng, L., Yu, F., Huang, P. Liu, G., Zhang, M., and Sun, R. (2025). Game-theoretic evolution in renewable energy systems: Advancing sustainable energy management and decision optimization in decentralized power markets, Renewable and Sustainable Energy Reviews, 217, 115776, ISSN 1364-0321, https://doi.org/10.1016/j.rser.2025.115776.
  10. Da Silva, R.F., Bellinello, M.M., de Souza, G.F.M., Antomarioni, S., Bevilacqua, M., and Ciarapica, F.E. (2021). Deciding a multicriteria decision-making (MCDM) method to prioritize maintenance work orders of hydroelectric power plants, Energies, 14(24), 8281. Doi: https://doi.org/10.3390/en14248281
APA
Özer, E. (2026). Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model. Karadeniz Fen Bilimleri Dergisi, 16(3), 1020-1046. https://doi.org/10.31466/kfbd.1767071
AMA
1.Özer E. Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model. KFBD. 2026;16(3):1020-1046. doi:10.31466/kfbd.1767071
Chicago
Özer, Ezgi. 2026. “Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model”. Karadeniz Fen Bilimleri Dergisi 16 (3): 1020-46. https://doi.org/10.31466/kfbd.1767071.
EndNote
Özer E (August 1, 2026) Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model. Karadeniz Fen Bilimleri Dergisi 16 3 1020–1046.
IEEE
[1]E. Özer, “Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model”, KFBD, vol. 16, no. 3, pp. 1020–1046, Aug. 2026, doi: 10.31466/kfbd.1767071.
ISNAD
Özer, Ezgi. “Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model”. Karadeniz Fen Bilimleri Dergisi 16/3 (August 1, 2026): 1020-1046. https://doi.org/10.31466/kfbd.1767071.
JAMA
1.Özer E. Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model. KFBD. 2026;16:1020–1046.
MLA
Özer, Ezgi. “Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model”. Karadeniz Fen Bilimleri Dergisi, vol. 16, no. 3, Aug. 2026, pp. 1020-46, doi:10.31466/kfbd.1767071.
Vancouver
1.Ezgi Özer. Weighted Criteria Analysis in Hydroelectric Energy Production: A Hybrid Fuzzy Entropy and Network-Based MCDM Model. KFBD. 2026 Aug. 1;16(3):1020-46. doi:10.31466/kfbd.1767071