Open Access iconOpen Access

ARTICLE

crossmark

Coronavirus Decision-Making Based on a Locally -Generalized Closed Set

M. A. El Safty1,*, S. A. Alblowi2, Yahya Almalki3, M. El Sayed4

1 Department of Mathematics and Statistics, College of Science, Taif University, Taif, 21944, Saudi Arabia
2 Department of Mathematics, College of Science, University of Jeddah, Jeddah, Saudi Arabia
3 Department of Mathematics, College of Science, King Khalid University, Abha, Saudi Arabia
4 Department of Mathematics, College of Science and Arts, Najran University, Najran, 66445, Saudi Arabia

* Corresponding Author: M. A. El Safty. Email: email

(This article belongs to this Special Issue: Intelligence 4.0: Concepts and Advances in Computational Intelligence)

Intelligent Automation & Soft Computing 2022, 32(1), 483-498. https://doi.org/10.32604/iasc.2022.021581

Abstract

Real-world applications now deal with a massive amount of data, and information about the world is inaccurate, incomplete, or uncertain. Therefore, we present in our paper a proposed model for solving problems. This model is based on the class of locally generalized closed sets, namely, locally simply* alpha generalized closed* sets and locally simply* alpha generalized closed** sets (briefly, -sets and -sets), based on simply* alpha open set. We also introduce various concepts of their properties and their relationship with other types, and we are studying several of their properties. Finally, we apply the concept of the simply* alpha open set to illustrate the importance of our method in decision-making for information systems about the infections of Coronavirus in humans. In fact, we were able to decide the impact factors of Coronavirus infection. The results were also programmed using the MATLAB program. Therefore, it is recommended that our proposed concept be used in future decision-making.

Keywords


Cite This Article

M. A. El Safty, S. A. Alblowi, Y. Almalki and M. El Sayed, "Coronavirus decision-making based on a locally -generalized closed set," Intelligent Automation & Soft Computing, vol. 32, no.1, pp. 483–498, 2022. https://doi.org/10.32604/iasc.2022.021581



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1491

    View

  • 794

    Download

  • 0

    Like

Share Link