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International Journal of Neutrosophic Science
Volume 21 , Issue 3, PP: 126-136 , 2023 | Cite this article as | XML | Html |PDF

Title

PCM with Linguistic Contradiction Degree Representations in Decision making on Academic Stress causing Factors

  N. Angel 1 * ,   P. Pandiammal 2 ,   N. Ramila Gandhi 3 ,   Nivetha Martin 4 ,   Florentin Smarandache 5

1  School of Mathematics, Madurai Kamaraj University, Madurai, Tamil Nadu, India
    (angelkeeri@gmail.com)

2  Department of Mathematics, GTN college of Arts & Science, Dindigul, Tamilnadu, India
    (pandiammal5781@gmail.com)

3  Department of Mathematics, PSNA College of Education and Technology, Dindigul
    (satrami@psnacet.edu.in)

4  Department of Mathematics, Arul Anandar College(Autonomous),Karumathur, Tamil Nadu, India
    (nivetha.martin710@gmail.com)

5  Emeritus Professor University of New Mexico, Mathematics, Physics, and Natural Science Division, USA
    (fsmarandache@gmail.com)


Doi   :   https://doi.org/10.54216/IJNS.210312

Received: February 17, 2023 Revised: May 28, 2023 Accepted: June 22, 2023

Abstract :

Plithogenic Cognitive Map (PCM) is the generalized form of Cognitive maps that has recently ebbed into the field of decision-making. The first developed PCM model comprises of factors, connection matrix with numeric contradiction degree between the factors. In this research work a PCM model with linguistic contradiction degree representations between the core and sub factors is developed to make the decision-making more comprehensive. The model formulated in this research work is illustrated with the factors causing academic stress to the students of digital educational system. Personal, Social, Economic and Institutional are considered as the core factors and the contradiction degree in linguistic sense is considered with respect to each of these core factors and ten sub factors. The obtained results on comparing with conventional models are highly promising and this model will certainly set new benchmarks of a comprehensive decision-making model.

Keywords :

PCM; linguistic variable; contradiction degree; academic stress

References :

[1] Abdel-Basset, M., Ding, W., Mohamed, R., & Metawa, N. (2020). An integrated plithogenic MCDM approach for financial performance evaluation of manufacturing industries. Risk Management, 22, 192-218.

[2] Ahmad, M. R., & Afzal, U. (2022). Mathematical modeling and AI based decision making for COVID-19 suspects backed by novel distance and similarity measures on plithogenic hypersoft sets. Artificial Intelligence in Medicine, 132, 102390.

[3] Ahmad, M. R., Saeed, M., Afzal, U., & Yang, M. S. (2020). A novel MCDM method based on plithogenic hypersoft sets under fuzzy neutrosophic environment. Symmetry, 12(11), 1855.

[4] Anusha, G., & Ramana, P. V. (2015). Analysis of Reasons for Stress on College Students using Combined Disjoint Block Fuzzy Cognitive Maps (CDBFCM). International Journal For Research In Emerging Science And Technology, 2, 16-21.

[5] Asghari, S., & Akbarpour Shirazi, M. (2023). Presenting Iran's future higher education scenarios using fuzzy cognitive maps. Research and Planning in Higher Education, 24(1), 1-26.

[6] Atanassov, K. (2016). Intuitionistic fuzzy sets. International journal bioautomation, 20, 1.

[7] Axelrod, R. (Ed.). (2015). Structure of decision: The cognitive maps of political elites. Princeton university press.

[8] Banathy, B. H. (1991). Cognitive mapping of educational systems for future generations. World Futures: Journal of General Evolution, 31(1), 5-17.

[9] Barón, H. B., Crespo, R. G., Pascual Espada, J., & Martínez, O. S. (2015). Assessment of learning in environments interactive through fuzzy cognitive maps. Soft Computing, 19, 1037-1050. [10] Chiang, D. F., Guerrero, S. A., & Sexton, E. C. (2023). Supporting Underrepresented Students in Health Sciences: Using a Fuzzy Cognitive Mapping Approach.

[11] Cole, J. R., & Persichitte, K. A. (2000). Fuzzy cognitive mapping: Applications in education. International journal of intelligent systems, 15(1), 1-25.

[12] Devadoss, A. V., Anand, M. C. J., & Bellarmin, A. J. (2013). A Study of Quality in Primary Education Combined Disjoint Block Neutrosophic Cognitive Maps (CDBNCM). In Indo-Bhutan International Conference On Gross National Happiness (Vol. 2, pp. 256-261).

[13] Devadoss, A. V., Anand, M. C. J., Felix, A., & Alexandar, S. (2015). A analysis of environmental education for the next generation using combined disjoint block fuzzy cognitive maps (CDBFCMS). In Indo-Bhutan international conference on gross national happiness (pp. 262-268).

[14] Dias, S. B., Hadjileontiadou, S. J., Hadjileontiadis, L. J., & Diniz, J. A. (2015). Fuzzy cognitive mapping of LMS users’ quality of interaction within higher education blended-learning environment. Expert systems with Applications, 42(21), 7399-7423.

[15] Gayen, S., Smarandache, F., Jha, S., Singh, M. K., Broumi, S., & Kumar, R. (2020). Introduction to plithogenic hypersoft subgroup. Infinite Study.

[16] Glykas, M. (Ed.). (2010). Fuzzy cognitive maps: Advances in theory, methodologies, tools and applications (Vol. 247). Springer Science & Business Media.

[17] Gómez, G. Á., Moya, J. V., Ricardo, J. E., & Sánchez, C. B. V. (2020). Evaluating Strategies of Continuing Education for Academics Supported in the Pedagogical Model and Based on Plithogenic Sets (Vol. 37). Infinite Study.

[18] Gordaliza, J. A., & Flórez, R. E. V. (2013). Using fuzzy cognitive maps to support complex environmental issues learning. In Proceedings of New Perspectives in Science Education Conference,.

[19] Gorelova, G. V., LYABACH, N. N., & KUIZHEVA, S. K. (2017). Application of Cognitive Modeling in the Study of the Interrelations between the Educational system and Society. Revista ESPACIOS, 38(56).

[20] Grida, M., Mohamed, R., & Zaied, A. N. H. (2021). A novel plithogenic MCDM framework for evaluating the performance of IoT based supply chain. Infinite Study.

[21] Kalaichelvi, A., & Gomathy, L. (2011). Application of neutrosophic cognitive maps in the analysis of the problems faced by girl students who got married during the period of study. Int. J. of Mathematical Sciences and Applications, 1(3).

[22] Kandasamy, W. V., & Smarandache, F. (2003). Fuzzy cognitive maps and neutrosophic cognitive maps. Infinite Study.

[23] Kosko, B. (1986). Fuzzy cognitive maps. International journal of man-machine studies, 24(1), 65-75.

[24] Luo, X., Wei, X., & Zhang, J. (2009, October). Game-based learning model using fuzzy cognitive map. In Proceedings of the first ACM international workshop on Multimedia technologies for distance learning (pp. 67-76).

[25] Mansouri, T., ZareRavasan, A., & Ashrafi, A. (2021). A learning fuzzy cognitive map (LFCM) approach to predict student performance. Journal of Information Technology Education: Research, 20, 221-243.

[26] Martin, N. (2022). Plithogenic SWARA-TOPSIS Decision Making on Food Processing Methods with Different Normalization Techniques. Advances in Decision Making, 69.

[27] Martin, N., & Smarandache, F. (2020). Plithogenic cognitive maps in decision making. Infinite Study.

[28] Martin, N., Priya, R., & Smarandache, F. (2021). New Plithogenic sub cognitive maps approach with mediating effects of factors in COVID-19 diagnostic model. Infinite Study.

[29] Mary, M. F. J., & Merlin, M. M. M. A Comparative Study Using Neutrosophic Cognitive Map and Triangular Fuzzy Cognitive Map for Analyzing The Factors for Quality Training of Elementary Education Student Teachers In Tamilnadu. Infinite Study.

[30] Merlin, M. (2015). Application of augmented fuzzy cognitive map in education. International Journal in IT & Engineering, 3(3), 39-54.

[31] Özçil, A., Tuş, A., Öztaş, G. Z., Adalı, E. A., & Öztaş, T. (2021). The novel integrated model of plithogenic sets and MAIRCA method for MCDM problems. In Intelligent and Fuzzy Techniques: Smart and Innovative Solutions: Proceedings of the INFUS 2020 Conference, Istanbul, Turkey, July 21-23, 2020 (pp. 733-741). Springer International Publishing.

[32] Peña-Ayala, A., & Sossa-Azuela, J. H. (2013). Decision making by rule-based fuzzy cognitive maps: an approach to implement student-centered education. In Fuzzy cognitive maps for applied sciences and engineering: From fundamentals to extensions and learning algorithms (pp. 107-120). Berlin, Heidelberg: Springer Berlin Heidelberg.

[33] Prakash, P., Jerlin, E., & Fernandes, B. (2014). A study on the causes for aversion to mathematics by engineering students using fuzzy cognitive maps (FCMs). International Journal of Innovative Research in Science, Engineering and Technology, 3(3), 10143-10150.

[34] Priya, R., Martin, N., & Kishore, T. E. (2022, May). Plithogenic cognitive analysis on instigating spiritual intelligence in smart age youth for humanity redemption. In AIP Conference Proceedings (Vol. 2393, No. 1, p. 020181). AIP Publishing LLC.

[35] Rana, S., Qayyum, M., Saeed, M., Smarandache, F., & Khan, B. A. (2019). Plithogenic fuzzy whole hypersoft set, construction of operators and their application in frequency matrix multi attribute decision making technique. Infinite Study.

[36] Thiruppathi, P., Saivaraju, N., & Ravichandran, K. S. (2010). A study on suicide problem using combined overlap block neutrosophic cognitive maps. International Journal of Algorithms, Computing and Mathematics, 3(4), 22-28.

[37] Ulutaş, A., Meidute-Kavaliauskiene, I., Topal, A., & Demir, E. (2021). Assessment of collaboration-based and non-collaboration-based logistics risks with plithogenic SWARA method. Logistics, 5(4), 82.


Cite this Article as :
Style #
MLA N. Angel, P. Pandiammal, N. Ramila Gandhi , Nivetha Martin, Florentin Smarandache. "PCM with Linguistic Contradiction Degree Representations in Decision making on Academic Stress causing Factors." International Journal of Neutrosophic Science, Vol. 21, No. 3, 2023 ,PP. 126-136 (Doi   :  https://doi.org/10.54216/IJNS.210312)
APA N. Angel, P. Pandiammal, N. Ramila Gandhi , Nivetha Martin, Florentin Smarandache. (2023). PCM with Linguistic Contradiction Degree Representations in Decision making on Academic Stress causing Factors. Journal of International Journal of Neutrosophic Science, 21 ( 3 ), 126-136 (Doi   :  https://doi.org/10.54216/IJNS.210312)
Chicago N. Angel, P. Pandiammal, N. Ramila Gandhi , Nivetha Martin, Florentin Smarandache. "PCM with Linguistic Contradiction Degree Representations in Decision making on Academic Stress causing Factors." Journal of International Journal of Neutrosophic Science, 21 no. 3 (2023): 126-136 (Doi   :  https://doi.org/10.54216/IJNS.210312)
Harvard N. Angel, P. Pandiammal, N. Ramila Gandhi , Nivetha Martin, Florentin Smarandache. (2023). PCM with Linguistic Contradiction Degree Representations in Decision making on Academic Stress causing Factors. Journal of International Journal of Neutrosophic Science, 21 ( 3 ), 126-136 (Doi   :  https://doi.org/10.54216/IJNS.210312)
Vancouver N. Angel, P. Pandiammal, N. Ramila Gandhi , Nivetha Martin, Florentin Smarandache. PCM with Linguistic Contradiction Degree Representations in Decision making on Academic Stress causing Factors. Journal of International Journal of Neutrosophic Science, (2023); 21 ( 3 ): 126-136 (Doi   :  https://doi.org/10.54216/IJNS.210312)
IEEE N. Angel, P. Pandiammal, N. Ramila Gandhi, Nivetha Martin, Florentin Smarandache, PCM with Linguistic Contradiction Degree Representations in Decision making on Academic Stress causing Factors, Journal of International Journal of Neutrosophic Science, Vol. 21 , No. 3 , (2023) : 126-136 (Doi   :  https://doi.org/10.54216/IJNS.210312)