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    A Fuzzy Decision-Making Methodology for Assessment of Solar Energy Plant Location Selection Criteria
    (Institute of Electrical and Electronics Engineers Inc., 2022) Bozkus, Emine; Kutlu Gündoıdu, Fatma; Karasan, Ali?; Işık, Gurkan; Kaya, İhsan
    According to the current technical knowledge, Renewable Energy Sources (RESs) have a crucial place for both industry and the environment considering their carbon emission values, risks and damage to the environment compared to fossil fuels and nuclear energy. Among them, Solar Energy (SE) is one of the cleanest RES due to its sustainable production environment and low carbon emission rates. Considering these advantages, Solar Energy Plants (SEPs) also have some disadvantages, such as land use, geographical conditions, and the supply of the components. Through that, SEP location selection is an essential and critical issue for the investors, which is related to many conflicting criteria. Moreover, exact evaluations for these criteria are not realistic when the system's locations and investment ecosystem are considered. Thus, the problem can be regarded as a complex decision-making problem due. Therefore, in this study, a preliminary investigation for calculating the importance of the criteria for the SEP location selection problem is analyzed using the Cognitive Mapping Method (CMM). To involve the uncertainty of the input data in the mathematical operations, Spherical Fuzzy Sets (SFSs) are integrated to increase the flexibility of the proposed method. The proposed method gives the ability to investigate complex relations between the criteria under highly uncertain environment, including indeterminacy and data inconsistency. The proposed methodology is applied to the Türkiye ecosystem, and the criterion "Land Acquisition"is determined as the most important one. © 2022 IEEE.
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    A Model Proposal for Smart Campus Investment Prioritization by Using Data Envelopment Analysis
    (Institute of Electrical and Electronics Engineers Inc., 2022) Çolak, Murat; Kutlu Gündoğdu, Fatma; Bozkus, Emine; Işık, Gurkan; Karasan, Ali?; Kaya, İhsan
    Smart campus (SC), one of the most highlighted concepts in the education system, is the utilization and combination of smart physical-digital spaces to provide improved, intelligent, and responsive services in a sustainable, productive, and creative environment for universities. Considering its multi-dimensional structure, investment in this area is a crucial strategic decision with many conflicting aspects. On the other hand, Data envelopment analysis (DEA) is a linear programming (LP) technique that quantifies the relative efficiency of decision-making unit (DMU) inputs into their outputs through a trial-and-error model. Through that, in this paper, by using the capability of the DEA model, an SC investment efficiency problem is considered in multiple ways. According to the literature review and experts' evaluations, four cost-based inputs are determined for the SC ecosystem. Based on the six outcomes, an application for the SC investment problem is carried out. Based on the results obtained, investments prioritized with the spending on classes and online teaching fulfilled the efficient rate input have the efficiency rate with one for all scenarios. Moreover, a scenario with equally distributed investments has the desired efficient rate equal to one. © 2022 IEEE.