M
Muhammet Deveci
Researcher at Naval Academy
Publications - 168
Citations - 3137
Muhammet Deveci is an academic researcher from Naval Academy. The author has contributed to research in topics: Computer science & Fuzzy logic. The author has an hindex of 20, co-authored 62 publications receiving 911 citations. Previous affiliations of Muhammet Deveci include National Defense University & Yıldız Technical University.
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WASPAS and TOPSIS based interval type-2 fuzzy MCDM method for a selection of a car sharing station
TL;DR: A Weighted Aggregated Sum Product Assessment (WASPAS) based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with interval type-2 fuzzy multi-criteria decision making (MCDM) model is proposed to provide a more accurate decision-making tool for problems involving high levels of uncertainty.
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Hydrogen mobility roll-up site selection using intuitionistic fuzzy sets based WASPAS, COPRAS and EDAS
Dorin Schitea,Muhammet Deveci,Mihaela Iordache,Kürşad Bilgili,İbrahim Zeki Akyurt,Ioan Iordache +5 more
TL;DR: An intuitionistic fuzzy set based multi-criteria decision making (MCDM) method, including WASPAS, COPRAS and EDAS is proposed for selecting the best location for hydrogen mobility roll-up site selection in Romania, finding Bucharest, the capital city to be the best starting point.
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A study on offshore wind farm siting criteria using a novel interval-valued fuzzy-rough based Delphi method
TL;DR: This study investigates the degree of importance of criteria affecting the optimal site selection of offshore wind farms using a novel Decision Making-Level Based Weight Assessment (LBWA) approach based on interval-valued fuzzy-rough numbers (IVFRN).
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Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland
TL;DR: An interval type-2 fuzzy sets based MCDM model is developed that integrates the score function with positive and negative solutions to achieve better results and it is shown that the proposed approach is superior in terms of stability and implementation as compared to its counterparts.
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Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS
TL;DR: The results show the viability of the proposed approach which yields Bozcaada as the appropriate site, when compared to and validated using the other multi-criteria decision-making techniques from the literature, including IRN based MABAC, WASPAS, and MAIRCA.