Multi-Perspective Strategic Analysis of Wind Energy Projects via AI-Integrated Quantum Fuzzy Recommender Approach
DOI:
https://doi.org/10.31181/jidmgc1120253Keywords:
Wind energy, Artificial intelligence, Fuzzy decision-making, Balanced scorecardAbstract
This manuscript aims to examine the most important critical indicators of feasibility analysis for wind energy projects. Within this context, experts are weighted using an artificial intelligence (AI) methodology. Secondly, missing evaluations are estimated via an expert recommender system. Thirdly, the balanced scorecard-based feasibility criteria are weighted with the help of Quantum Picture Fuzzy Rough Sets (QPFR)-based M-SWARA. Finally, selected project feasibility items for wind energy firms are ranked using QPFR-VIKOR. The main contribution of this study is the use of an artificial intelligence technique in the proposed model to compute the weights of the experts. This approach provides an opportunity to achieve more effective results. Customer expectation is identified as the most essential criterion in the balanced scorecard-based feasibility analysis. Environmental assessment of long-term effects is the most critical project feasibility item for wind energy firms. Cost-benefit analysis, considering economic, sectoral, and project-based conditions, also plays a critical role in this respect.
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