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Öğe A comprehensive approach to evaluate risk mitigation strategies in offshore wind farms using spherical fuzzy decision making analysis(Elsevier Ltd, 2024) Ayyildiz, E.; Erdogan, M.The escalating impact of global warming, primarily exacerbated by carbon emissions from conventional energy sources, has prompted significant advancements in offshore wind energy as a pivotal avenue for sustainable development. Amid the surging interest in renewable energy, offshore wind-farms have emerged as a promising solution. To ensure their efficient and effective operation, it becomes imperative to systematically identify and mitigate potential risks. This study addresses the critical need to systematically prioritize risk reduction strategies for offshore wind farms, a problem that has not been comprehensively explored in the literature. A multi-criteria analysis has been adopted to simultaneously evaluate the contradictory criteria in the evaluation process. The novelty of this study lies in its integration of spherical fuzzy sets with multi-criteria decision-making (MCDM) techniques to handle uncertainties and evaluate contradictory criteria simultaneously. As a result of all this analysis, the most critical risks for offshore wind-farms and risk mitigation strategies that can be adopted within the determined risks have been revealed. The main findings reveal that turbine underperformance, disruption of habitats, and grid connection issues are the most critical risks. Furthermore, a combination of robust design and engineering and collaboration and partnerships emerged as the most effective risk mitigation strategies. © 2024 Elsevier LtdÖğe Forecasting COVID-19 recovered cases with Artificial Neural Networks to enable designing an effective blood supply chain(Elsevier Ltd, 2021) Ayyildiz, E.; Erdogan, M.; Taskin, A.This study introduces a forecasting model to help design an effective blood supply chain mechanism for tackling the COVID-19 pandemic. In doing so, first, the number of people recovered from COVID-19 is forecasted using the Artificial Neural Networks (ANNs) to determine potential donors for convalescent (immune) plasma (CIP) treatment of COVID-19. This is performed explicitly to show the applicability of ANNs in forecasting the daily number of patients recovered from COVID-19. Second, the ANNs-based approach is further applied to the data from Italy to confirm its robustness in other geographical contexts. Finally, to evaluate its forecasting accuracy, the proposed Multi-Layer Perceptron (MLP) approach is compared with other traditional models, including Autoregressive Integrated Moving Average (ARIMA), Long Short-term Memory (LSTM), and Nonlinear Autoregressive Network with Exogenous Inputs (NARX). Compared to the ARIMA, LSTM, and NARX, the MLP-based model is found to perform better in forecasting the number of people recovered from COVID-19. Overall, the findings suggest that the proposed model is robust and can be widely applied in other parts of the world in forecasting the patients recovered from COVID-19. © 2021 Elsevier LtdÖğe Literature analysis of the location selection studies related to the waste facilities within MCDM approaches(Springer, 2024) Ayyildiz, E.; Erdogan, M.The increase in waste and related environmental problems is one of the major problems compromising health and environmental quality in urban and rural areas. There are a number of policies that can be implemented to reduce waste, but since it cannot be completely eliminated, recycling and disposal facilities for waste will always be required. Researchers and professionals are currently grappling with the issue of where to locate waste facilities. In the light of all this information, a literature review is presented so that researchers can easily access and systematically review previous studies on the waste facility location selection problem. At this point, in order to reduce the reviewed studies to a reasonable level and to conduct a more organized research, this literature research has conducted within the framework of multi-criteria decision-making (MCDM) approaches, which is one of the most applied methods in location selection problems. The subsequent strengths, weaknesses, opportunities, and threats (SWOT) analysis delves into the strengths, weaknesses, opportunities, and threats in the field, offering a concise guide for future research in waste facility location selection problem. The SWOT analysis highlights the strengths of global environmental awareness and versatile MCDM approaches, while addressing weaknesses in emerging technology integration and potential biases. Opportunities for interdisciplinary collaboration and integration of sustainability metrics provide strategic pathways, but threats such as regulatory changes and limited funding underscore challenges. This analysis serves as a concise guide for future research in waste facility location selection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.Öğe Prioritization of Influence Factors for Selecting E–Learning Systems(Springer, 2021) Karasan, A.; Erdogan, M.COVID-19 pandemic affects not only daily life activities but also traditional education systems. Based on the current developments, to stick by their academic calendars, most of the educational institutions continue their classes via online channels. Since the selection of the most appropriate e–learning platform depends on multi–criteria, the evaluation of this selection process can be dealt with decision support systems. In this study, cognitive mapping extended with intuitionistic fuzzy sets is introduced for prioritizing the e–learning platform selection factors under fuzzy environment based on the multi–expert judgments. Based on the results, infrastructure and ease of use are determined as the most effective factors. For further studies, a sensitivity analysis based on the initial vector determination can be studied to check its effect on the outputs. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe SWOT Analysis Integrated Interval Type-2 Triangular Fuzzy AHP: Application on e-Scooter Adaptation in Turkiye(Springer Science and Business Media Deutschland GmbH, 2023) Ayyildiz, E.; Erdogan, M.As an alternate mode of transportation, the use of shared bicycle and scooter systems, which are now being brought to the forefront under the term micromobility, has recently been increasing. Among them, electric scooters called e-scooters have started to be preferred frequently due to their ease of use. With this study, the factors to be considered for the adaptation of e-scooters have been determined and an e-scooter situation analysis has been carried out for Turkiye. For this reason, the factors brought together within the scope of the SWOT analysis have been examined and their priority degrees have been calculated. The factors considered in the SWOT analysis have been weighted with the interval type-2 fuzzy analytic hierarchy process (AHP). As a result, the most important and least important factors have been determined. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
