Fuzzy SSPO-separation Axioms and Fuzzy α-SSPO Compactness
DOI:
https://doi.org/10.29020/nybg.ejpam.v17i2.5062Keywords:
Fuzzy separation axioms, Fuzzy compactness, Fuzzy strongly semi pre-open setAbstract
In this paper we will introduce the concept of new separation axioms named fuzzy SSPO-separation axioms by using the fuzzy strong semi preopen sets and we will also introduce and investigate properties of (alpha)-SSPO compactness. We will define and investigate relation between fuzzy separation axioms, fuzzy pre-separation axioms and different forms of fuzzy continuous mappings. We will also investigate the existence of a countable base of fuzzy strong semi preopen sets, we will define the concept of SSPO separability, the concept of (alpha)-SSPO Lindelof sets and examine their properties. With the concept of fuzzy strong semi pre-continuity, SSPO-irresolute continuous mappings and other forms of fuzzy continuity, we will investigate the new concept of fuzzy compactness and its properties in regards to the mentioned mappings.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 European Journal of Pure and Applied Mathematics
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Upon acceptance of an article by the European Journal of Pure and Applied Mathematics, the author(s) retain the copyright to the article. However, by submitting your work, you agree that the article will be published under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). This license allows others to copy, distribute, and adapt your work, provided proper attribution is given to the original author(s) and source. However, the work cannot be used for commercial purposes.
By agreeing to this statement, you acknowledge that:
- You retain full copyright over your work.
- The European Journal of Pure and Applied Mathematics will publish your work under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
- This license allows others to use and share your work for non-commercial purposes, provided they give appropriate credit to the original author(s) and source.