Akademik Veri Yönetim Sistemi
Iranian Journal of Fuzzy Systems, cilt.22, sa.3, ss.55-86, 2025 (SCI-Expanded, Scopus)
The performance of transparent solar panel projects is affected by both technological and environmental and economic factors. However, the most important items should be identified for the efficient use of limited resources and effective risk management. There are few studies in the literature determining these factors. Because of this situation, businesses cannot direct their resources correctly and cannot create an effective strategy. A molecular fuzzy decision-making system is created to determine the most successful alternative investment policies for these projects to satisfy this gap in the literature. Various techniques are integrated in this model to reach the most effective solutions, such as molecular fuzzy sets to handle uncertainties, q-learning algorithm to weight experts, least square optimization (LSO) to calculate criteria weights and multi-objective particle swarm optimization (MOPSO) to rank investment strategies. The main contribution of this study is proposing an innovative molecular fuzzy decision-making model that manages uncertainties more effectively to select the most appropriate investment strategies for transparent solar panel investments. Considering molecular fuzzy sets allows for more accurate modelling of uncertainties and subjective evaluations. The results show that the most critical investment criterion for transparent solar panel investments is the regional solar radiation level.