262 149
Full Length Article
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

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

1  Affiliation :  Department of Advanced Mathematical Science, Saveetha School of Engineering, Saveetha University, Saveetha Institute of Medical and Technical Sciences, Chennai-602105, India

    Email :  gsm.maths@gmail.com


2  Affiliation :  Department of Advanced Mathematical Science, Saveetha School of Engineering, Saveetha University, Saveetha Institute of Medical and Technical Sciences, Chennai-602105, India

    Email :  palanimaths86@gmail.com


3  Affiliation :  Department of Mathematics, Bharath Institute of Higher Education and Research, Tamil Nadu, Chennai-600073, India

    Email :  arulmozhiems@gmail.com


4  Affiliation :  Fuzzy Algebras and Decision-Making Problems Research Unit, Department of Mathematics, School of Science, University of Phayao, Mae Ka, Mueang, Phayao 56000, Thailand

    Email :  aiyared.ia@up.ac.th


5  Affiliation :  Laboratory of Information Processing, Faculty of Science Ben M’Sik, Universit´s Hassan II, BP 7955 Casablanca, Morocco

    Email :  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

References :

[1] A. B. Al-Nafee, S. Broumi, L. A. Al Swidi, n-valued refined neutrosophic crisp sets, International Journal

of Neutrosophic Science, vol. 17, no. 2, pp. 87–95, 2021.

[2] S. Alkhazaleh, A. R. Salleh, N. Hassan, Possibility fuzzy soft set, Advances in Decision Sciences, vol.

2011, Article ID 479756, 18 pages, 2011.

[3] K. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, vol. 20, no. 1, pp. 87–96, 1986.

[4] B. C. Cuong, Picture fuzzy sets, Journal of Computer Science and Cybernetics, vol. 30, no. 4, 409–420,

2014.

[5] B. C. Cuong, V. Kreinovich, Picture fuzzy sets a new concept for computational intelligence problems,

Proceedings of 2013 Third World Congress on Information and Communication Technologies (WICT

2013), IEEE, pp. 1–6, 2013.

[6] F. Karaaslan, Possibility neutrosophic soft sets and PNS-decision making method, Applied Soft Computing,

vol. 54, 403–414, 2017.

[7] R. Jansi, K. Mohana, F. Smarandache, Correlation measure for Pythagorean neutrosophic sets with T and

F as dependent neutrosophic components, Neutrosophic Sets and Systems, vol. 30, 202–212, 2019.

[8] M. Lathamaheswari, S. Broumi, F. Smarandache, S. Sudha, Neutrosophic perspective of neutrosophic

probability distributions and its application, International Journal of Neutrosophic Science, vol. 17, no.

2, 96–109, 2021.

[9] P. K. Maji, R. Biswas, A. R. Roy, Fuzzy soft set, Journal of Fuzzy Mathematics, vol. 9, no. 3, 589–602,

2001.

[10] P. K. Maji, R. Biswas, A. R. Roy, On intuitionistic fuzzy soft set, Journal of Fuzzy Mathematics, vol. 9,

no. 3, 677–692, 2001.

[11] P. Majumdar, S. K. Samantab, Generalized fuzzy soft sets, Computers and Mathematics with Applications,

vol. 59, 1425–1432, 2010.

[12] D. Molodtsov, Soft set theory first results, Computers and Mathematics with Applications, vol. 37, 19–31,

1999.

[13] M. Palanikumar, K. Arulmozhi, On various ideals and its applications of bisemirings, Gedrag and Organisatie

Review, vol. 33, no, 2, pp. 522–533, 2020.

[14] M. Palanikumar, K. Arulmozhi, On intuitionistic fuzzy normal subbisemirings of bisemirings, Nonlinear

Studies, vol. 28, no. 3, pp. 717–721, 2021.

[15] M. Palanikumar, K. Arulmozhi, On new ways of various ideals in ternary semigroups, Matrix Science

Mathematic, vol. 4, no. 1, pp. 6–9, 2020.

[16] M. Palanikumar, K. Arulmozhi, (α, β)-Neutrosophic subbisemiring of bisemiring, Neutrosophic Sets

and Systems, vol. 48, pp. 368–385, 2022.

[17] M. Palanikumar, K. Arulmozhi, On various tri-ideals in ternary semirings, Bulletin of the International

Mathematical Virtual Institute, vol. 11, no. 1, pp. 79–90, 2021.

[18] M. Palanikumar, K. Arulmozhi, On Pythagorean normal subbisemiring of bisemiring, Annals of Communications

in Mathematics, vol. 4, no. 1, pp. 63–72, 2021.

[19] M. Palanikumar, K. Arulmozhi, On various almost ideals of semirings, Annals of Communications in

Mathematics, vol. 4, no. 1, pp. 17–25, 2021.

[20] X. D. Peng, Y. Yang, J. P. Song, Pythagorean fuzzy soft set and its application, Computer Engineering,

vol. 41, no. 7, 224–229, 2015.

[21] S. Alkhazaleh, A. R. Salleh, Generalized interval valued fuzzy soft set, Journal of Applied Mathematics,

vol. 2012, Article ID 870504, 18 pages, 2012.

[22] F. Smarandache, A unifying field in logics. Neutrosophy: neutrosophic probability, set and logic, American

Research Press, Rehoboth, 1999.

[23] S. Dhouib, S. Broumi, M. Lathamaheswari, Single valued trapezoidal neutrosophic travelling salesman

problem with novel greedy method, the dhouib matrix TSP1, International Journal of Neutrosophic Science,

vol. 17, no. 2, 144–157, 2021.

[24] R. R. Yager, Pythagorean membership grades in multi criteria decision-making, IEEE Transactions on

Fuzzy Systems, vol. 22, no. 4, pp. 958–965, 2014.

[25] Y. Yang, C. Liang, S. Ji, T. Liu, Adjustable soft discernibility matrix based on picture fuzzy soft sets and

its applications in decision making, Journal of Intelligent and Fuzzy Systems, vol. 29, 1711–1722, 2015.

[26] L. A. Zadeh, Fuzzy sets, Information and Control, vol. 8, no. 3, pp. 338–353, 1965.


Cite this Article as :
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) : 166-176 (Doi   :  https://doi.org/10.54216/IJNS.190112)