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    A new integrated methodology for constructing linguistic pythagorean fuzzy statements for decision making problems
    (IOS PRESS, 2022) Işık, Gürkan; Kaya, Ihsan
    As a combining concept of Pythagorean fuzzy sets (PFSs) and linguistic fuzzy sets (FSs), linguistic PFSs (LPFSs) has been suggested in the literature to deal with the uncertain and inconsistent information in multi-criteria decision making (MCDM) process. The LPFSs based procedure has been built by assuming that the experts make assessments suitable with PFS. It does not provide a mechanism to ensure the suitability of the assessments with theory of PFSs but there are other type of non-standard fuzzy sets such as Neutrosophic sets (NSs) used for modeling with inconsistent information. The main motivation of this study is to offer an assessment collection method to guarantee that the input statements will be Pythagorean fuzzy linguistic expressions. As a second motivation, it is aimed to extend the PFS method for the fuzzy modeling of the other type of decision-making problems apart from MCDM which do not require aggregation and comparison operations and continue with precise fuzzy modeling (PFM). The third motivation of this study is to offer enhancements on the LPFSs method to increase the sensitivity of the modeling while protecting the interpretability. For these purposes, a newmethodology based on LPFSs has been proposed and applied on a decision-making problem in a comparative way.
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    Design of acceptance sampling plans based on interval valued neutrosophic sets
    (Springer, 2023) Isik, Guerkan; Kaya, Ihsan
    Acceptance sampling plans (ASPs) are conducted by inspecting a small set of items instead of all outputs. Although traditional ASPs use certain plan parameters, it is clear that quality characteristics or definitions may not be certain in some real case applications because of uncertainties. The fuzzy set theory (FST) is a popular technique to model uncertainty in the engineering problems. It is known that ASPs have been successfully formulated based on FST in the literature. However, the uncertainty is generally more complex in cases including human evaluations. Neutrosophic sets (NSs) that is one of the fuzzy set extensions bring some advantages to manage more complicated uncertainties in quality problems especially uncertainty based on human's hesitancy. Since the NSs include three terms as truthiness (t), indeterminacy (i), and falsity (f), they can successfully model the human thinking and inspectors' evaluations under uncertainty. In this paper, traditional attribute ASPs have been extended based on interval NSs to combine the computational and interpretational advantages of the interval statistics with the advantages of NSs. Additionally, two well-known distributions for ASPs called Binomial and Poisson distributions are redesigned by using NSs. For this aim, NSs are converted to interval NSs by using a-cut technique and some characteristic functions of ASPs such as acceptance probability (P-a), average sample number (ASN), and average total inspection (ATI) have been designed for single and double ASPs based on interval NSs. The proposed ASPs based on NSs have been tested on some numerical applications from a manufacturing process, and results obtained based on real cases have been compared.
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    Evaluation of Potential Locations for Hydropower Plants by Using a Fuzzy Based Methodology Consists of Two-Dimensional Uncertain Linguistic Variables
    (Inst Information Science, 2022) Kaya, Ihsan; Isik, Gurkan; Karasan, Ali; Gundogdu, Fatma Kutlu; Baracli, Hayri
    Hydropower is one of the most efficient renewable energy sources for the sustaina-bility of the environment if the plant location is well decided. The plant location should satisfy different criteria emerged by a wide range of criteria, consisting of law, environ-ment, and the expectations of the investors and residents. Some of these criteria can be conflicting. Some of them may also be in a relationship with each other. Moreover, they may be evaluated in a system that contains uncertainty consisting of a lack of information, impreciseness in the data, and human hesitancy. These aspects can be a powerful effect on the location selection of the hydropower plants and are considered in mathematical formu-lations. So, the problem can be considered as a multi-criteria decision-making (MCDM) problem under uncertainty. In this study, by considering the types of uncertainties, impre-ciseness of the available data, and hesitancy of the experts, an integrated MCDM method-ology consisting of DEMATEL, cognitive mapping, and TOPSIS methods has been ex-tended based on hesitant fuzzy z-numbers. Then the proposed methodology has been ap-plied for the evaluation of potential locations for hydropower plants in Turkey. For this aim, a hierarchical structure consisting of twenty-nine criteria and four alternative loca-tions has been determined for the assessment by combining literature analysis and expert knowledge. In the first stage, the criteria Availability of Water, Annual flow, Tech-nology, Capacity, and Annual energy production have been demonstrated as the most influential criteria for location selection. Then, based on the z-number fuzzy TOPSIS method, the most appropriate alternative for the construction location has been determined in Turkey. The findings have been checked in terms of validation and flexibility of the given decisions by applying sensitivity and comparative analyses.