Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ4Comparison of the Performance of Machine Learning Methods with Intuitionistic Fuzzy Decision Making for Effective Fake News Detection
Tuğrul, Feride
In this paper, the success of machine learning models applied to two datasets consisting of fake news was examined. The performance of these methods was measured using Accuracy, Precision, Recall, and F1-Score. Evaluation metrics for all models were calculated using TF-IDF and N-gram TF-IDF for Dataset 1 and Dataset 2, respectively. In continuation of the study, a decision-making mechanism was created to measure the success of machine learning methods. The success of these models was compared by creating a decision-making mechanism using intuitionistic fuzzy sets. The PROMETHEE method was used here. In the first stage of the study, the dataset samples evaluated were expressed using classical sets, while in the second stage, the success of the models according to the metrics was expressed using intuitionistic fuzzy values. This was to minimize the uncertainty in the model success results. The results obtained in the first stage of the study were evaluated in the second stage using a decision-making mechanism. In this mechanism, machine learning models represent the alternatives, while classification metrics represent the criteria. When evaluating machine learning models, experts provide subjective opinions based on each classification metric to determine the successful model.
- MakaleYalnız künye2025The Position of Metaheuristic Optimization Methods in Psychiatric Practice: A Bibliometric Analysis
Tuğrul, Feride; Can, Umit
Mental diseases affect billions of people worldwide to varying degrees. This poses a risk to public health. Although the levels and effects of diseases vary, in general, mental diseases prevent people from having a healthy relationship with themselves and their environment and prevent them from living their daily lives efficiently. Individuals who move away from the comfort of daily life face many difficulties in their social and professional lives. People with long-term mental disorders may also experience physiological disorders due to stress. When this situation is not treated and prevented, it becomes a public health problem. Therefore, centers such as health institutions, research centers, and universities operating in the field of health carry out many studies to detect and treat mental disorders. These methods include traditional methods, but today, they also include artificial intelligence-supported methods. AI-powered methods are used for early diagnosis and treatment of mental illnesses by analyzing large amounts of mental illness data of various types. Researchers are also using metaheuristic optimization algorithms to improve the performance of these methods. These optimization methods, which seek fast and high-performance solutions to very complex nonlinear problems, are increasing the success of machine learning and deep learning methods. Nonetheless, there is no distinct bibliometric analysis demonstrating the quantity and quality of research in this domain for scholars. This study aims to fill this gap in this field and to be a preliminary guide for researchers.
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İncele - MakaleAçık Erişim2025Research on Comparative Analysis of Intuitionistic Fuzzy PROMETHEE and TOPSIS Methods
Tuğrul, Feride
IF based MCDM methods are a current research area that attracts the attention of many re-searchers. In this study, studies examining Offset, Laserjet and Inkjet printing performances of recycled papers using the intuitionistic fuzzy-based PROMETHEE and TOPSIS methods were revised with a new perspective. The most important difference that distinguishes this study from other studies is the creation of a system that simultaneously evaluates all the criteria and the elimination of uncertainty thanks to intuitionistic fuzzy sets. For this purpose, a comparative analysis of the IF based- PROMETHEE and TOPSIS methods was made. The results of the PROMETHEE method, which was created according to numerical data, and the TOPSIS method, which reflects the opinions in linguistic terms, were discussed. Evaluating all the criteria at the same time is what makes the study original. As a result; findings that will shed light on the relevant literature and give researchers a new perspective were obtained.
- EditoryalYalnız künye2025Scopus SJRQ4Preface
Castillo, Oscar; Çuvalcıoğlu, Gökhan; Tuğrul, Feride
- Kitap BölümüYalnız künye2025Scopus SJRQ4Examination of Recycled Papers Using an Intuitionistic Fuzzy Set-Based MCDM
Tuğrul, Feride
Multi-criteria decision making (MCDM) methods are used in combination with intuitionistic fuzzy sets offer very favorable results to decision makers. Intuitionistic fuzzy set-based MCDM methods defined in this direction were utilized in many application areas. In this study, recycled papers were examined separately according to Cyan, Magenta and Yellow colors. Paper samples, which passed through a total of 4 recycling stages, were evaluated according to their L, a, and b values. The decision making mechanism established in the study was observed that provides effective results in the fields such as paper quality, print quality, recycling, etc.
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