International Journal of Neutrosophic Science

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2690-6805ISSN (Online) 2692-6148ISSN (Print)

On Refined Netrusophic Fractional Calculus

Mohamed Nedal Khatib , Ahmed Hatip

Depending on the geometric isometry (AH-Isometry), it has been proven that every Neutrosophic real function is equivalent to three real functions. Then, the foundation of the Refined Netrusophic calculus was established, where new definitions of Refined Netrusophic integration and Refined Netrusophic differentiation were introduced, along with some illustrative examples. Following that, definitions for the Refined Netrusophic gamma function and Refined Netrusophic beta function were presented to pave the way towards achieving the desired goal, which is Refined Netrusophic Fractional calculus.

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Vol. 24 Issue. 2 PP. 08-18, (2024)

Reliability Function Estimated for Generalized Exponential Rayleigh Distribution Under Type-I Censored Data and Fuzzy Data

Zainab A. Aldraji , Rehab Noori shalan

In this paper, maximum likelihood estimation method (MLEM), one of the most well-liked and frequently applied classic methods, is used to estimate the two scale and one shape parameters of the Generalized Exponential-Rayleigh distribution for type-I censored data, which is one of the most Rights censored data. Based on an iterative process to get approximated values for these two scale parameters and one shape parameter using the Newton-Raphson method to locate estimate value for these parameters by using the simulation procedure utilizing monte-Carlo technique to find Reliability function underneath various sample sizes and the initial values are different for the parameters for all estimated parameters of Generalized Exponential-Rayleigh by implement the initial value in the MATLAP program, Subsequently, conducting a comparative analysis between the estimated reliability function and its non-estimated counterpart employing the mean squares error methodology. In the last finding the pdf function f (t), reliability function R (t) and hazard function h (t) for simulation data. Also, we provide some examples to clarify how can we apply our results on fuzzy data tables

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Vol. 24 Issue. 2 PP. 19-29, (2024)

Plithogenic Sociogram based Plithogenic Cognitive Maps Approach in Sustainable Industries

N. Angel , Sulbha Raorane , N. Ramila Gandhi , R. Priya , P. Pandiammal , Nivetha Martin

The theory of Plithogeny is primarily attribute based. Plithogenic Sociogram (PS) and Plithogenic cognitive maps (PCM) are distinct decision-making approaches developed to deal with attributes. This paper proposes an integrated decision-making model combining the approaches of PS with PCM and this sets the beginning of new genre of PCM. The development of this model is applied in investigating the association between the factors pertinent to the promotion of sustainable industries.  This work also compares the working of the proposed integrated model of PCM with PS and the independent working of PCM model. The results are more promising to the proposed integrated approach and this paper strongly emphasises the efficacy of this hybrid approach. The blended model of PCM with PS is efficient in handling complex decision circumstances and this approach shall be extended to other kinds of Plithogenic representations.

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Vol. 24 Issue. 2 PP. 30-41, (2024)

Enhancing Project Selection with Neutrosophic TOPSIS: Navigating Uncertainty in Post-Pandemic Decision-Making

Frantz Dimitri V. Barragan , Felipe Garcés Cordova , María J. Calderon Velásquez , Layal Kallach

This article explores the implementation of Neutrosophic TOPSIS, an advanced decision-making framework that extends classical and fuzzy set theories to handle the complexities of project selection amid uncertainty and indeterminacy. Neutrosophic sets are characterized by three parameters: truth, indeterminacy, and falsehood, which allow for a nuanced assessment of alternatives against defined criteria. Utilizing neutrosophic scales and expert evaluations, this method prioritizes projects by efficiently balancing multiple truth levels and addressing specific challenges such as judicial process optimization and labor education enhancement. The case study within the article demonstrates the application of Neutrosophic TOPSIS to select the most suitable project for improving labor relations and judicial efficiency in a post-pandemic world. The methodology proved effective in identifying the Digital Platform for Labor Education project as the optimal solution, given its alignment with strategic objectives and potential to handle identified challenges robustly. Future work could integrate Neutrosophic TOPSIS with other decision-making models and expand its application to more complex scenarios, potentially incorporating automated tools for a broader and more dynamic evaluation process.

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Vol. 24 Issue. 2 PP. 42-49, (2024)

Fusion of Centrality Measures with D-OWA in Neutrosophic Cognitive Maps to Develop a Composite Centrality Indicator

Byron J. Chulco Lema , Carlos Javier L. Chapeta , Rosa E. Chuga Quemac , Layal Kallach

This study utilized Neutrosophic Cognitive Maps (NCMs) integrated with the D-OWA operator to analyze the nutritional rights of pregnant women in Ecuador, with a focus on the crucial role of nutrition education. The innovative application of the D-OWA operator enabled the computation of a composite centrality measure by merging key centrality indicators—degree, closeness, and betweenness—each appropriately weighted according to its relevance to the analysis. This methodology provided a sophisticated evaluation of the factors impacting maternal nutrition, demonstrating how combining various centrality measures offers a deeper and more comprehensive insight into the dynamics of complex systems. The calculated composite centrality measures revealed the system’s intricate structure, pinpointing critical nodes and pathways that could be targeted most effectively through interventions. The findings underscore the significant benefits of using composite centrality measures to enhance decision-making in public health and other sectors characterized by complexity and uncertainty. The potential for refining and expanding this approach in future research suggests that it could be further supported by technological advancements, enabling more efficient analysis and scalability across diverse complex systems.

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Vol. 24 Issue. 2 PP. 50-57, (2024)

Enhancing Decision-Making in Complex Environments: Integrating AHP, Delphi, and Neutrosophic Logic

Marcia Esther E. Heredia , Jorge Washigton S. Andachi , Nemis García Arias , Saziye Yaman

The integration of the Analytic Hierarchy Process (AHP), the Delphi method, and neutrosophic logic provides a powerful framework for complex decision-making, allowing for an enhanced handling of uncertainties and multiple criteria that characterizes many strategic planning and policy formulation scenarios. AHP’s structured approach helps decompose decision-making into manageable sub-problems, while the Delphi method facilitates expert consensus through iterative rounds, enriching the decision-making process with diverse expert insights. The inclusion of neutrosophic logic allows for better representation and processing of uncertainty, offering a flexible way to handle indeterminate and contradictory information. This robust methodology not only improves the precision of decisions but also adapts to the nuanced requirements of multifaceted decision environments. Future research could benefit from integrating these methods with technological advancements like artificial intelligence to automate and optimize the decision-making process further. Applying this integrated approach in various sectors such as healthcare, environmental management, and urban planning could also provide valuable insights into its effectiveness and scalability.

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Vol. 24 Issue. 2 PP. 58-67, (2024)