Yazar "Samanta, Sovan" seçeneğine göre listele

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    A Study on Linguistic Z-Graph and Its Application in Social Networks
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024) Mahapatra, Rupkumar; Samanta, Sovan; Pal, Madhumangal; Allahviranloo, Tofigh; Allahviranloo, Tofigh
    This paper presents a comprehensive study of the linguistic Z-graph, which is a novel framework designed to analyze linguistic structures within social networks. By integrating concepts from graph theory and linguistics, the linguistic Z-graph provides a detailed understanding of language dynamics in online communities. This study highlights the practical applications of linguistic Z-graphs in identifying central nodes within social networks, which are crucial for online businesses in market capture and information dissemination. Traditional methods for identifying central nodes rely on direct connections, but social network connections often exhibit uncertainty. This paper focuses on using fuzzy theory, particularly linguistic Z-graphs, to address this uncertainty, offering more detailed insights compared to fuzzy graphs. Our study introduces a new centrality measure using linguistic Z-graphs, enhancing our understanding of social network structures. © 2024 by the authors.
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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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    Link Prediction in Co-Authorship Network Under Fuzziness and Application in Biomedical Analysis
    (Tsinghua University Press, 2024) Das, Kousik; Maity, Ananta; De, Kajal; Mondal, Sukumar; Samanta, Sovan; Allahviranloo, Tofigh
    We aim to predict links in fuzzy social networks, where the existing methods based on common neighbors of two nodes are not effective. These methods are local measures that only work when the shortest distance between two nodes is less than or equal to two. Our method can handle cases where the shortest distance is between three and five. We define the concepts of link strength and path strength in a network and propose an algorithm for predicting links. We illustrate our method with a numerical example in a co-authorship network and discuss application areas in biomedical. © 2009 Tsinghua University Press.
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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.
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    New concept of centrality measurement in fuzzy social networks
    (IOS Press BV, 2024) Mahapatra, Rupkumar; Samanta, Sovan; Pal, Madhumangal
    The most critical task of a social network is to identify a central node. Numerous methods for determining centrality are documented in the literature. It contributes to online commerce by disseminating news, advertisements and other content via central nodes. Existing methods capture the node's direct reachability. This study introduces a novel method for quantifying centrality in a fuzzy environment. This measurement takes into account the reachability of nodes and their direct connections. Several critical properties have been demonstrated. A small Facebook network is used to illustrate the issue. Additionally, appropriate tables and graphs present a comparative study with existing methods for centrality measurement. © 2024-IOS Press. All rights reserved.