Mass expert group decision-making based on q-learning and molecular fuzzy logic for floating renewable energy materials investments

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Elsevier B.V.

Erişim Hakkı

info:eu-repo/semantics/openAccess

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Organizasyon Birimi
Yönetim Bilimleri Fakültesi, İşletme Bölümü
Küresel rekabete ayak uydurmak ve sürdürülebilir olmak isteyen tüm şirketler ve kurumlar, değişimi doğru bir şekilde yönetmek, teknolojinin gerekli kıldığı zihinsel ve operasyonel dönüşümü kurumlarına hızlı bir şekilde adapte etmek zorundadırlar.

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Özet

Floating renewable energy systems refer to energy projects deployed on water surfaces, playing a vital role in future energy strategies by promoting the use of sustainable resources. These systems reduce dependency on fossil fuels, meet growing energy demands, and ensure energy security by enabling countries to produce their own energy. The performance of these investments is influenced by technical and environmental factors. Despite their importance, there is a lack of comprehensive studies identifying the most critical factors affecting performance, creating a gap in the literature. This study addresses this gap by developing an innovative decision-making model using information gain, Q-learning, molecular fuzzy cognitive maps, and molecular ranking techniques. Hence, the main purpose is to identify the most critical determinants and optimal strategies for floating renewable energy investments, providing valuable guidance for decision-makers and investors. The study contributes to the literature by providing a structured criterion set for decision-makers. The findings obtained from the study highlight the optimization of areas with multiple uses. According to this criterion, it is possible to use other energy systems in an area other than floating systems. This situation also brings a cost advantage. It also supports purposes such as environmental protection and preventing water waste. Another important criterion, environmental integration, is to create an energy production system that is compatible with the living creatures living here by protecting the natural ecosystem on the water surface where the floating systems will be installed. Furthermore, it introduces novel methodologies that are rarely used in existing studies, such as calculating expert importance weights and modelling complex factor interactions. By addressing these gaps, the study offers both theoretical and practical advancements, ensuring more efficient and sustainable investment strategies in floating renewable energy systems. It is concluded that space optimization with multi-use potential and environmental integration with ecosystem protection are found as the most critical determinants. Tidal energy systems and wave energy converters are the most effective investment alternatives.

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Anahtar Kelimeler

Clean Energy, Energy Independence, Energy Investments, Floating Renewable Energy System

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Next Materials

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Scopus Q Değeri

Cilt

8

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Kou, G., Dinçer, H., Yüksel, S., Acar, M., Eti, S. & Hacıoğlu, Ü. (2025). Mass expert group decision-making based on q-learning and molecular fuzzy logic for floating renewable energy materials investments. Next Materials, 8, 1-15. https://www.doi.org/10.1016/j.nxmate.2025.100747

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