Muhammet Deveci
55734383000
Publications - 5
New distance measures of complex Fermatean fuzzy sets with applications in decision making and clustering problems
Publication Name: Information Sciences
Publication Date: 2025-01-01
Volume: 686
Issue: Unknown
Page Range: Unknown
Description:
Complex Fermatean fuzzy sets (CFFSs) integrate the ideas of complex fuzzy sets and Fermatean fuzzy sets, where the membership, non-membership, and hesitancy degrees are all complex numbers, allowing the express uncertain information more flexibly and comprehensively. However, how to reasonably measure the discrepancies between CFFSs in decision-making remains an open task. This paper presents a series of new distance measures of CFFSs and their weighted versions based on Hamming, Euclidean, Hausdorff, and Hellinger distances. On this basis, we explore some outstanding properties that the proposed measures satisfy (i.e., boundedness, nondegeneracy, symmetry, and triangular inequality) and demonstrate their effectiveness through several examples. Furthermore, we design a decision-making algorithm as well as a clustering algorithm based on the proposed measures and verify the performance of the proposed measures through several applications.
Open Access: Yes
Artificial intelligence-based expert weighted quantum picture fuzzy rough sets and recommendation system for metaverse investment decision-making priorities
Publication Name: Artificial Intelligence Review
Publication Date: 2024-10-01
Volume: 57
Issue: 10
Page Range: Unknown
Description:
There should be some improvements to increase the performance of Metaverse investments. However, businesses need to focus on the most important actions to provide cost effectiveness in this process. In summary, a new study is needed in which a priority analysis is made for the performance indicators of Metaverse investments. Accordingly, this study aims to evaluate the main determinants of the performance of the metaverse investments. Within this context, a novel model is created that has four different stages. The first stage is related to the prioritizing the experts with artificial intelligence-based decision-making method. Secondly, missing evaluations are estimated by expert recommendation system. Thirdly, the criteria are weighted with Quantum picture fuzzy rough sets-based (QPFR) M-Step-wise Weight Assessment Ratio Analysis (SWARA). Finally, investment decision-making priorities are ranked by QPFR VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje). The main contribution of this study is the integration of the artificial intelligence methodology to the fuzzy decision-making approach for the purpose of computing the weights of the decision makers. Owing to this condition, the evaluations of these people are examined according to their qualifications. This situation has a positive contribution to make more effective evaluations. Organizational effectiveness is found to be the most important factor in improving the performance of metaverse investments. Similarly, it is also identified that it is important for businesses to ensure technological improvements in the development of Metaverse investments. On the other side, the ranking results indicate that regulatory framework is the most critical alternative in this regard.
Open Access: Yes
Novel α-divergence measures on picture fuzzy sets and interval-valued picture fuzzy sets with diverse applications
Publication Name: Engineering Applications of Artificial Intelligence
Publication Date: 2024-10-01
Volume: 136
Issue: Unknown
Page Range: Unknown
Description:
Currently, many studies have developed distance or divergence measures between intuitionistic fuzzy sets (IFSs) and interval-valued fuzzy sets (IvFSs). As a generalization of IFSs, picture fuzzy sets (PFSs) provide a more nuanced representation of uncertain and ambiguous information. Interval-valued picture fuzzy sets (IvPFSs) combine the concepts of IvIFSs and PFSs, providing a highly effective means of representing and processing uncertain, ambiguous and incomplete information. How to better measure the differences between PFSs and IvPFSs is still an open issue. This paper proposes some novel α-divergence measures for PFSs and IvPFSs, respectively. We demonstrate the basic properties of the proposed divergence measures, including non-negativity, non-degeneracy and symmetry. Besides, we analyze some special cases of the proposed divergence measures that degenerate into or are related to several well-known divergences. Then, we construct some numerical examples to demonstrate the effectiveness of the proposed measures concerning existing measures. Finally, the proposed α-divergence measures are applied to pattern recognition, multi-attribute decision-making (MADM) and clustering, demonstrating that these measures possess a high confidence level and can produce trustworthy results, especially in comparable situations.
Open Access: Yes
Holistic evaluation of energy transition technology investments using an integrated recommender system and artificial intelligence-based fuzzy decision-making approach
Publication Name: Results in Engineering
Publication Date: 2024-09-01
Volume: 23
Issue: Unknown
Page Range: Unknown
Description:
The most essential criteria should be determined in the selection of the suitable energy transition technologies due to budget deficit problem. Therefore, it is necessary to identify the most important criteria in energy transition technology selection. Therefore, a new study is needed to determine the most prominent issues in the correct selection of energy transition technologies. The purpose of this study is to identify the most appropriate energy transition technology alternative. Within this framework, a novel artificial intelligence (AI)-based fuzzy decision-making model has been presented. In the first part, the experts are prioritized by the help of AI methodology. In the next section, missing evaluations of energy transition technology investments are estimated via expert recommender system. Thirdly, the weights of the criteria for energy transition technology selection are computed by quantum picture fuzzy rough sets (QPFR) M-Stepwise Weight Assessment Ratio Analysis (SWARA). At the final stage, selected energy transition technology alternatives are ranked via QPFR-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). The main contribution of this study is the integration of AI technique to the proposed model. Similar to this issue, using M-SWARA methodology in the process of criteria weighting increases the quality of the findings. This methodology helps to consider the impact relation map of the criteria. The findings demonstrate that the most important factor is cost-effectiveness of energy transition. Similarly, it is also found that the local ecosystem is the second most significant issue. On the other side, the ranking results denote that compact renewable systems for small scale production is the most optimal solution of energy transition technology alternatives.
Open Access: Yes
A Schweizer–Sklar power Bonferroni aggregation operator under p,q-QOFS for vendor selection based on GRA-DEMATEL-MEREC
Publication Name: Mathematics and Computers in Simulation
Publication Date: 2026-11-01
Volume: 249
Issue: Unknown
Page Range: 784-812
Description:
This study aims to support decision-making in vendor selection for water supply problem which is often complex and uncertain. Vendor selection involves multiple criteria, including technical capability, quality of proposals, financial strength, and risk management. Evaluating vendors in water supply problem is therefore a challenging task. To address this challenge, this research proposes a systematic framework for vendor assessment based on the judgements of technical experts, environmental scientists, local committees, project managers, and government authorities. Thereafter, we introduce a new integrated approach that synergizes power Bonferroni aggregation operators and Schweizer–Sklar operation with p,q-quasirung orthopair fuzzy information and grey relational analysis, providing a robust framework to tackle real-life challenges. Moreover, the proposed model integrates the MEREC (MEthod based on the Removal Effects of Criteria) and DEMATEL (DEcision-MAking Trial and Evaluation Laboratory) methods to derive more precise and reliable weights for both attributes and experts. This robust framework enhances multi-attribute decision-making by enabling decision-making to make well-informed choices and providing structured, accurate solutions that minimize uncertainty and enhance decision quality. What is more, using a numerical example based on the process of considering problem, we construct a novel decision-making method. Finally, we include sensitivity analysis and a comparison between the existing approaches and the proposed method in this study.
Open Access: Yes
