International Journal of Neutrosophic Science

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

Neutrosophic Integrals by Reduction Formula and Partial Fraction Methods for Indefinite Integrals

A. Manshath , E. Kungumaraj , E. Lathanayagam , M. C. Joe Anand , Nivetha Martin , Elangovan Muniyandy , S. Indrakumar

Neutrosophic mathematics is a branch of mathematics that deals with ambiguity, indeterminacy, and incompleteness in mathematical objects and procedures. To account for Neutrosophic uncertainty, several mathematical concepts—including the reduction formula, partial fractions, and area finding—are extended in this field. The Neutrosophic reduction formula is a technique for summarising simpler words from a complex mathematical expression when the coefficientss a nd/or values may be ambiguous or unknown. By taking the potential of insufficient information into account, expands the traditional reduction formula. A rational function can be broken down using the Neutrosophic partial fraction into several simpler expressions, where the coefficients and/or values may be ambiguous or unknown. By considering, this expands the traditional partial fraction. The potential for inaccurate information. A method for calculating the area under a curve where the curve's form or position may be unknown or ambiguous is area finding via neutrosophic integration. By considering the potential of having insufficient information, this expands the traditional area of searching. These ideas can be used in fields like decision-making, expert systems, and artificial intelligence and are crucial for handling problems in the real world that entail uncertainty, indeterminacy, and incompleteness.

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Vol. 23 Issue. 1 PP. 08-16, (2024)

δ-separation Axioms on Fuzzy Hypersoft Topological Spaces

P. Surendra , A. Vadivel , K. Chitirakala

In this article, the concept of fuzzy hypersoft δ (resp. semi, pre, δ semi & δ pre)-separation axioms in fuzzy hypersoft topological spaces are introduced by developing fuzzy hypersoft δ (resp. semi, pre, δ semi & δ pre)-neighbourhood with respect to fuzzy hypersoft points. Also, the properties and relations between fuzzy hypersoft δ (resp. semi, pre, δ semi & δ pre)- Ti- spaces (i = 0, 1, 2, 3, 4) are discussed.

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Vol. 23 Issue. 1 PP. 17-26, (2024)

Effective Neutrosophic Soft Expert Set and Its Application

Sumyyah Al-Hijjawi , Abd Ghafur Ahmad , Shawkat Alkhazaleh

The neutrosophic soft set emerges as a highly valuable and efficient adaptation of soft sets, specifically addressing parameterized values of alternatives. However, numerous decision-making algorithms rooted in neutrosophic soft sets often neglect the external factors impacting their effectiveness. This paper introduces the innovative concept of an effective neutrosophic soft expert set, meticulously crafted to encapsulate external influences on both neutrosophic soft sets and expert opinions within a unified model. This eliminates the necessity for additional operations. Notably, our groundbreaking approach seamlessly amalgamates the strengths of the neutrosophic soft expert set and the effective set, resulting in heightened efficiency and realism in this domain. The article comprehensively explores the fundamental operations of an effective neutrosophic soft expert set, elucidating these processes through apt examples. Finally, the paper showcases the practical application of this concept in decision-making problems, providing algorithms and illustrative examples to underscore its efficacy.

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Vol. 23 Issue. 1 PP. 27-50, (2024)

Fuzzy Logic Used to Solve ODEs of Second Order Under Neutrosophic Initial Conditions

Sahar M. Jabbar , Azal Mera , Ameera N. Alkiffai

The Mohand transform method, which has the benefit of unit preservation property over the well-established Laplace transform method, is used in this study to solve the ordinary differential equation of second order with neutrosophic numbers as initial conditions. Moreover, the solution obtained at different  –cut .

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Vol. 23 Issue. 1 PP. 51-58, (2024)

Neutrosophic Control Chart for Rayleigh Quality with Applications To Wind Speed Data

Fuad S. Alduais , Zahid Khan , Muhammad Waseem

The application of neutrosophic statistics provides a novel approach to dealing with uncertain and imprecise data problems. In this study, we present an improved method called neutrosophic Rayleigh exponential weighted moving average  chart. The  chart is an extension of the traditional  model and can be applied in various fields. The proposed  scheme is designed to enhance the detection capability of the traditional  chart. The key features of the suggested chart are discussed, highlighting its capability to handle vague, indeterminate, and fuzzy data situations. We evaluate the performance of the proposed scheme by analyzing the designated limits and charting parameters for different sample sizes. Moreover, we establish the performance metrics of the  chart such as neutrosophic run length ( ) and neutrosophic power curve ( ).Performance metrics demonstrate that the  chart is highly sensitive to persistent shifts in the scaling parameter of the neutrosophic Rayleigh distribution. Monte Carlo simulations are conducted to compare the suggested scheme with the existing model. A comparative study indicates that the proposed chart outperforms the competing design, particularly in detecting smaller shifts. Finally, we provide a charting structure for the proposed design using daily average wind speed data, which can be used as a practical implementation guideline for real-world applications.

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Vol. 23 Issue. 1 PP. 59-72, (2024)

Neutrosophic Laplace Distribution with Properties and Applications in Decision Making

Ahmedia Musa M. Ibrahim , Zahid Khan

This paper introduces the concept of the neutrosophic Laplace distribution ( ), a probability distribution derived from the Laplace distribution. The  offers a versatile framework for describing various real-world problems. We highlight the neutrosophic extension of the Laplace distribution and explore its applications in different areas. Extensive investigations into the mathematical properties of the distribution are presented, including the derivation of its probability density function, mean, variance, raw moment, skewness, and kurtosis. To estimate the parameters of the , we employ the method of maximum likelihood (ML) estimation within a neutrosophic environment. Furthermore, we conduct a simulation study to assess the effectiveness of the maximum likelihood approach in estimating the parameters of this new distribution. The findings demonstrate the potential of the  in modeling and analyzing real-world phenomena. Eventually, some illustrative examples related to system reliability are provided to clarify further the implementation of the neutrosophic probabilistic model in real-world problems.

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Vol. 23 Issue. 1 PP. 73-84, (2024)