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International Journal of Neutrosophic Science
Volume 19 , Issue 3, PP: 16-28 , 2022 | Cite this article as | XML | Html |PDF

Title

Analyzing the Sustainability of Industry Affected in COVID-19 Pandemic Scenario Using Cosine Similarity Measure under SVPNS and PNN Model

Authors Names :   Priyanka Majumder   1 *     Florentin Smarandache   2  

1  Affiliation :  Department of Basic Science and Humanities, Techno College of Engineering Agartala, Tripura, India

    Email :  majumderpriyanka94@yahoo.com


2  Affiliation :  University of New Mexico, Mathematics Department, 705 Gurley Ave., Gallup, NM 87301, USA

    Email :  fsmarandache@gmail.com



Doi   :   https://doi.org/10.54216/IJNS.190302

Received: May 18, 2021 Accepted: October 06, 2022

Abstract :

COVID-19 outbreak is a reminder of the fact that the pandemics have happened in the past and will also occur in the future. The COVID-19 not only has affected the economy; but also it has affected the livelihood, which leads to the changes in businesses. This study aims to identify the most significant indicator (or parameter) that impacts the sustainability of industries. The study should also develop a real-time monitoring system for the sustainability of industries affected by COVID 19. In this work, the Polynomial Neural Network (PNN) and cosine similarity measure under SVPNS (Single-Valued Pentapartitioned Neutrosophic Set) environment have found their use in analyzing the sustainability of the industry.

Keywords :

COVID-19; SVPNS; cosine similarity measure; Polynomial Neural Network; sustainability.

References :

[1] Consejo de la Unión Europea. European Council-Council of the European Union, Recuperado el.

[2] T. A. Ghebreyesus. World Health Organization. WHO Director-General‟s opening remarks at

the media briefing on COVID-19-25 May 2020.

[3] Saglietto, Andrea, Fabrizio D‟Ascenzo, Giuseppe Biondi Zoccai, and Gaetano Maria De Ferrari.

COVID-19 in Europe: the Italian lesson, The Lancet 395, no. 10230 (2020): 1110-1111.

[4] Tobías, Aurelio, Cristina Carnerero, Cristina Reche, Jordi Massagué, Marta Via, María Cruz

Minguillón, Andrés Alastuey, and Xavier Querol. Changes in air quality during the lockdown in

Barcelona (Spain) one month into the SARS-CoV-2 epidemic, Science of the total

environment 726 (2020): 138540.

[5] Ministry of Health, Covid 19 (2020), https://covid19.saglik.gov.tr/.

[6] Hashmi, Masooma Raza, Muhammad Riaz, and Florentin Smarandache. m-polar neutrosophic

generalized weighted and m-polar neutrosophic generalized Einstein weighted aggregation

operators to diagnose coronavirus (COVID-19), Journal of Intelligent & Fuzzy Systems 39, no. 5

(2020): 7381-7401.

[7] Acter, Thamina, Nizam Uddin, Jagotamoy Das, Afroza Akhter, Tasrina Rabia Choudhury, and

Sunghwan Kim. Evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

as coronavirus disease 2019 (COVID-19) pandemic: A global health emergency, Science of the

Total Environment 730 (2020): 138996.

[8] Read, Jonathan M., Jessica RE Bridgen, Derek AT Cummings, Antonia Ho, and Chris P. Jewell.

Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic

predictions, medrxiv (2020).

[9] Cássaro, Fábio AM, and Luiz F. Pires. Can we predict the occurrence of COVID-19 cases?

Considerations using a simple model of growth, Science of the Total Environment 728 (2020):

138834.

[10] UNESCO (2020), https://en.unesco.org/

[11] Ferguson, Neil M., Daniel Laydon, Gemma Nedjati-Gilani, Natsuko Imai, Kylie Ainslie, Marc

Baguelin, Sangeeta Bhatia et al. Impact of non-pharmaceutical interventions (NPIs) to reduce

COVID-19 mortality and healthcare demand, (2020).

[12] Ji, Qiang, Dayong Zhang, and Yuqian Zhao. Searching for safe-haven assets during the COVID-

19 pandemic, International Review of Financial Analysis 71 (2020): 101526.

[13] ILO Director general speech

[14] Zadeh, L. A., Fuzzy Sets. Inform. Control 8 (1965).

[15] Atanassov, K. Intuitionistic fuzzy sets. fuzzy sets and systems 20 (1), 87-96, (1986).

[16] Smarandache, Florentin. Neutrosophy: neutrosophic probability, set, and logic: analytic

synthesis & synthetic analysis. (1998).

[17] Wang, Haibin, Florentin Smarandache, Yanqing Zhang, and Rajshekhar Sunderraman. Single

valued neutrosophic sets. Infinite study, 2010.

[18] Mallick, Rama, and Surapati Pramanik. Pentapartitioned neutrosophic set and its properties. Vol.

36. Infinite Study, 2020.

[19] Majumder, Priyanka, Suman Das, Rakhal Das, and Binod Chandra Tripathy. Identification of the

most significant risk factor of COVID-19 in economy using cosine similarity measure under

SVPNS-environment, Neutrosophic Sets and Systems 46 (2021): 112-127.

[20] Das, Rakhal, Anjan Mukherjee, and Binod Chandra Tripathy. Application of neutrosophic

similarity measures in Covid-19, Annals of Data Science 9, no. 1 (2022): 55-70.

[21] Martin, Nivetha, R. Priya, and Florentin Smarandache. New Plithogenic sub cognitive maps

approach with mediating effects of factors in COVID-19 diagnostic model. Infinite Study, 2021.

[22] Eyo, Imo, Jeremiah Eyoh, and Uduak Umoh. "On the prediction of COVID-19 time series: an

intuitionistic fuzzy logic approach." Journal of Fuzzy Extension and Applications 2.2 (2021):

171-190.

[23] Arora, Shaveta, Renu Vadhera, and Bharti Chugh. "A decision-making system for Corona

prognosis using fuzzy inference system." Journal of fuzzy extension and applications 2.4 (2021):

344-354.

[24] TuncalıYaman, T., and G. R. Akkartal. "How warehouse location decisions changed in medical

sector after pandemic? a fuzzy comparative study." Journal of fuzzy extension and

application 3.1 (2022): 81-95.

[25] Eyo, Imo Jeremiah, et al. "Hybrid intelligent parameter tuning approach for COVID-19 time

series modeling and prediction." Journal of Fuzzy Extension and Applications 3.1 (2022): 64-80.

[26] Abbas, M., Asghar, M., Guo, Y. (2022). Decision-Making Analysis of Minimizing the Death

Rate Due to COVID-19 by Using q-Rung Orthopair Fuzzy Soft Bonferroni Mean Operators.

Journal of Fuzzy Extension and Applications, (), -. doi: 10.22105/jfea.2022.335045.1214

[27] Javanbakht, T., and Sh Chakravorty. "Prediction of human behavior with TOPSIS." Journal of

fuzzy extension and applications 3.2 (2022): 109-125.

[28] Ejegwa, P. A., and D. Zuakwagh. "Fermatean fuzzy modified composite relation and its

application in pattern recognition." Journal of fuzzy extension and applications 3.2 (2022): 140-

151.

[29] Ivakhnenko, Alexey Grigorevich. The group method of data handling, a rival of the method of

stochastic approximation, Soviet Automatic Control 13, no. 3 (1968): 43-55.

[30] Hartmann, Nathaniel N., and Bruno Lussier. Managing the sales force through the unexpected

exogenous COVID-19 crisis, Industrial Marketing Management 88 (2020): 101-111.

[31] Paul, Sanjoy Kumar, and Priyabrata Chowdhury. A production recovery plan in manufacturing

supply chains for a high-demand item during COVID-19, International Journal of Physical

Distribution & Logistics Management 51, no. 2 (2020): 104-125.

[32] Borjas, George J., and Hugh Cassidy. The adverse effect of the COVID-19 labor market shock

on immigrant employment, No. w27243. National Bureau of Economic Research, 2020.

[33] Mohammed, Mazin Abed, Karrar Hameed Abdulkareem, Alaa S. Al-Waisy, Salama A. Mostafa,

Shumoos Al-Fahdawi, Ahmed Musa Dinar, Wajdi Alhakami et al. Benchmarking methodology

for selection of optimal COVID-19 diagnostic model based on entropy and TOPSIS methods,

Ieee Access 8 (2020): 99115-99131.


Cite this Article as :
Priyanka Majumder , Florentin Smarandache, Analyzing the Sustainability of Industry Affected in COVID-19 Pandemic Scenario Using Cosine Similarity Measure under SVPNS and PNN Model, International Journal of Neutrosophic Science, Vol. 19 , No. 3 , (2022) : 16-28 (Doi   :  https://doi.org/10.54216/IJNS.190302)