ORCID
A. A. Salama: 0000-0003-2300-615X
Huda E. Khalid: 0000-0002-6599-120X
Ahmed K. Essa: 0000-0001-6153-9964
Ahmed G. Mabrouk: 0000-0002-4220-5341
Article Type
Research Article
Abstract
Neutrosophic topological spaces (NTS) offer a novel framework for uncertainty modeling by incorporating degrees of truth, indeterminacy, and falsity. This paper investigates the potential applications of NTS in computer science. We provide background on neutrosophic sets and their extension to topological spaces. We then explore how NTS could be used for uncertainty modeling in data analysis (e.g., handling noisy data in sensor networks), pattern recognition (e.g., improving image classification with imprecise features), and information retrieval (e.g., enhancing search results by considering relevance uncertainty). We discuss the challenges associated with applying NTS and highlight promising areas for future research, such as developing efficient algorithms for NTS operations. Overall, this paper aims to stimulate further exploration of how neutrosophic topological spaces can contribute to advancements in various computer science domains.
Keywords
Neutrosophic Sets, Topological Space, Uncertainty Modeling, Computer Science, Data Analysis, pattern recognition, Information Retrieval
How to Cite
Salama, A. A.; Khalid, Huda E.; Essa, Ahmed K.; and Mabrouk, Ahmed G.
(2024)
"Exploring the Potential of Neutrosophic Topological Spaces in Computer Science,"
Neutrosophic Systems with Applications: Vol. 21:
Iss.
1, Article 5.
DOI: https://doi.org/10.61356/j.nswa.2024.21366
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.