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International Journal of Neutrosophic Science
Volume 19 , Issue 1, PP: 166-176 , 2022 | Cite this article as | XML | Html |PDF

Title

Agriculture Production Decision Making using Generalized q-Rung Neutrosophic Soft Set Method

  G. Shanmugam 1 * ,   M. Palanikumar 2 ,   K. Arulmozhi 3 ,   Aiyared Iampan 4 ,   Said Broumi 5

1  Department of Advanced Mathematical Science, Saveetha School of Engineering, Saveetha University, Saveetha Institute of Medical and Technical Sciences, Chennai-602105, India
    (gsm.maths@gmail.com)

2  Department of Advanced Mathematical Science, Saveetha School of Engineering, Saveetha University, Saveetha Institute of Medical and Technical Sciences, Chennai-602105, India
    (palanimaths86@gmail.com)

3  Department of Mathematics, Bharath Institute of Higher Education and Research, Tamil Nadu, Chennai-600073, India
    (arulmozhiems@gmail.com)

4  Fuzzy Algebras and Decision-Making Problems Research Unit, Department of Mathematics, School of Science, University of Phayao, Mae Ka, Mueang, Phayao 56000, Thailand
    (aiyared.ia@up.ac.th)

5  Laboratory of Information Processing, Faculty of Science Ben M’Sik, Universit´s Hassan II, BP 7955 Casablanca, Morocco
    (broumisaid78@gmail.com)


Doi   :   https://doi.org/10.54216/IJNS.190112

Received: April 19, 2022 Accepted: August 13, 2022

Abstract :

This paper introduces the generalized q-rung neutrosophic soft set (GqRNSSS) theory and its use to solve actual

problems. We also define a few operations that make use of the GqRNSSS. The GqRNSSS is constructed

by generalizing both the Pythagorean neutrosophic soft set (PyNSSS) and Pythagorean fuzzy soft set (PyFSS).

We give a method for agricultural output that is based on the proposed similarity measure of GqRNSSS. If two

GqRNSSS are compared, it can be determined whether or not a person produces good agricultural output. We

support a strategy for dealing with the decision-making (DM) problem that makes use of the generalized qrung

soft set model. In this article, we discuss the application of a similarity measure between two GqRNSSS

in agricultural output. Show how they can be successfully applied to challenges with uncertainty.

Keywords :

GqRNSSS; PyFSS; decision making problem

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Cite this Article as :
Style #
MLA G. Shanmugam, M. Palanikumar, K. Arulmozhi, Aiyared Iampan, Said Broumi. "Agriculture Production Decision Making using Generalized q-Rung Neutrosophic Soft Set Method." International Journal of Neutrosophic Science, Vol. 19, No. 1, 2022 ,PP. 166-176 (Doi   :  https://doi.org/10.54216/IJNS.190112)
APA G. Shanmugam, M. Palanikumar, K. Arulmozhi, Aiyared Iampan, Said Broumi. (2022). Agriculture Production Decision Making using Generalized q-Rung Neutrosophic Soft Set Method. Journal of International Journal of Neutrosophic Science, 19 ( 1 ), 166-176 (Doi   :  https://doi.org/10.54216/IJNS.190112)
Chicago G. Shanmugam, M. Palanikumar, K. Arulmozhi, Aiyared Iampan, Said Broumi. "Agriculture Production Decision Making using Generalized q-Rung Neutrosophic Soft Set Method." Journal of International Journal of Neutrosophic Science, 19 no. 1 (2022): 166-176 (Doi   :  https://doi.org/10.54216/IJNS.190112)
Harvard G. Shanmugam, M. Palanikumar, K. Arulmozhi, Aiyared Iampan, Said Broumi. (2022). Agriculture Production Decision Making using Generalized q-Rung Neutrosophic Soft Set Method. Journal of International Journal of Neutrosophic Science, 19 ( 1 ), 166-176 (Doi   :  https://doi.org/10.54216/IJNS.190112)
Vancouver G. Shanmugam, M. Palanikumar, K. Arulmozhi, Aiyared Iampan, Said Broumi. Agriculture Production Decision Making using Generalized q-Rung Neutrosophic Soft Set Method. Journal of International Journal of Neutrosophic Science, (2022); 19 ( 1 ): 166-176 (Doi   :  https://doi.org/10.54216/IJNS.190112)
IEEE G. Shanmugam, M. Palanikumar, K. Arulmozhi, Aiyared Iampan, Said Broumi, Agriculture Production Decision Making using Generalized q-Rung Neutrosophic Soft Set Method, Journal of International Journal of Neutrosophic Science, Vol. 19 , No. 1 , (2022) : 166-176 (Doi   :  https://doi.org/10.54216/IJNS.190112)