An integrated fuzzy-neuro model for evaluation of energy system of naval vessels at concept design
Ships and Offshore Structures, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1080/17445302.2026.2748916
- Dergi Adı: Ships and Offshore Structures
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, INSPEC, Natural Science Collection (ProQuest), Earth, Atmospheric, & Aquatic Science Collection (ProQuest), Engineering Source (EBSCO), Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
- Anahtar Kelimeler: artificial neural networks, decision-making, design of naval ships, electrical power system of naval ships, fuzzy analytic hierarchy process, Propulsion of naval ships
- Yıldız Teknik Üniversitesi Adresli: Evet
Özet
The selection of a suitable energy system, including propulsion and electrical power systems, is a critical decision during the concept design phase of naval ships. Interrelated and conflicting criteria, along with uncertainty, complicate this process and necessitate a comprehensive decision-support model. This study proposes a decision model integrating Artificial Neural Networks (ANN) with Fuzzy Set Theory (FST). The Fuzzy Analytic Hierarchy Process (FAHP), based on Buckley’s geometric mean method, was employed to determine ANN inputs while addressing uncertainty, ambiguity, and subjectivity in expert judgments. The relative weights of alternatives for each criterion were mapped as ANN synaptic weights. The model was applied to an offshore patrol vessel (OPV) equipped with Wageningen C4-40 series propellers. Four propulsion alternatives, including conventional diesel and hybrid configurations, were evaluated against nine criteria. The results indicated that the conventional single-diesel-engine configuration achieved the highest ranking, demonstrating the model’s applicability to naval energy-system selection.