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    A Fuzzy Logic Inference Model for the Evaluation of the Effect of Extrinsic Factors on the Transmission of Infectious Diseases
    (Mdpi, 2024) Kalampakas, Antonios; Samanta, Sovan; Bera, Jayanta; Das, Kinkar Chandra
    COVID-19 is a contagious disease that poses a serious risk to public health worldwide. To reduce its spread, people need to adopt preventive behaviours such as wearing masks, maintaining physical distance, and isolating themselves if they are infected. However, the effectiveness of these measures may depend on various factors that differ across countries. This paper investigates how some factors, namely outsiders' effect, life expectancy, population density, smoker percentage, and temperature, influence the transmission and death rate of COVID-19 in ninety-five top-affected countries. We collect and analyse the data of COVID-19 cases and deaths using statistical tests. We also use fuzzy logic to model the chances of COVID-19 based on the results of the statistical tests. Unlike the conventional uniform weighting of the rule base in fuzzy logic, we propose a novel method to calculate the weights of the rule base according to the significance of the factors. This study aims to provide a comprehensive and comparative analysis of the factors of COVID-19 transmission and death rates among different countries.
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    Multicriteria Group Decision Making Based on TODIM and PROMETHEE II Approaches with Integrating Quantum Decision Theory and Linguistic Z Number in Renewable Energy Selection
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024) Mandal, Prasenjit; Mrsic, Leo; Kalampakas, Antonios; Allahviranloo, Tofigh; Samanta, Sovan
    Decision makers (DMs) are often viewed as autonomous in the majority of multicriteria group decision making (MCGDM) situations, and their psychological behaviors are seldom taken into account. Once more, we are unable to prevent both positive and negative flows of varying alternative preferences due to the nature of attributes or criteria in complicated decision-making problems. However, DMs’ perspectives are likely to affect one another in complicated MCGDM issues, and they frequently use subjective limited rationality while making decisions. The multicriteria quantum decision theory-based group decision making integrating the TODIM-PROMETHEE II strategy under linguistic Z-numbers (LZNs) is designed to overcome the aforementioned problems. In our established technique, the PROMETHEE II controls the positive and negative flows of distinct alternative preferences, the TODIM method manages the experts’ personal regrets over a criterion, and the quantum probability theory (QPT) addresses human cognition and behavior. Because LZNs can convey linguistic judgment and trustworthiness, we provide expert LZNs for their viewpoints in this work. We determine the criterion weights for each expert after first obtaining their respective expert weights. Second, to represent the limited rational behaviors of the DMs, the TODIM-PROMETHEE II approach is introduced. It is employed to determine each alternative’s dominance in both positive and negative flows. Third, a framework for quantum possibilistic aggregation is developed to investigate the effects of interference between the views of DMs. The views of DMs are seen in this procedure as synchronously occurring wave functions that affect the overall outcome by interfering with one another. The model’s efficacy is then assessed by a selection of renewable energy case studies, sensitive analysis, comparative analysis, and debate. © 2024 by the authors.