A Novel Approach for Normal Parameter Reduction Algorithm of Soft Set Using Unit Similarity Matrix

E. E.  Elijah; U. F.  Muhammad

doi:10.6084/zenodo.8218007

A Novel Approach for Normal Parameter Reduction Algorithm of Soft Set Using Unit Similarity Matrix

E. E. Elijah Department of Mathematical Sciences, Bauchi State University, Gadau, Nigeria
U. F. Muhammad Department of Mathematics, Nigerian Army University, Biu, Nigeria

DOI: https://doi.org/10.6084/zenodo.8218007

Keywords: Soft Set, Algorithm, Normal Parameter Reduction;, Unit Similarity parameters, Unit Similarity Matrix

Abstract

Soft set has been introduced to deal with uncertainty involved in many real life problems. However, most of the time, these decision-making problems involve less important and redundant parameters, which make the decision making process more complex and challenging. Therefore, in this study the concept of reduct of a soft set is discussed and a new algorithm is developed for normal parameter reduction (NPR) base on the unit similarity matrix. Finally, the propose algorithm is compared with previous parameter reduction algorithms in terms of computational complexity.

Published

2023-07-25

How to Cite

Elijah, E. E., & Muhammad, U. F. (2023). A Novel Approach for Normal Parameter Reduction Algorithm of Soft Set Using Unit Similarity Matrix. International Journal of Mathematical Sciences and Optimization: Theory and Applications, 9(1), 43 - 58. https://doi.org/10.6084/zenodo.8218007

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Issue

Vol 9 No 1 (2023)

Section

Articles

This work is licensed under a Creative Commons Attribution 4.0 International License.

This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, adaptation, and reproduction in any medium, provided that the original work is properly cited.