✨
AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
A finite intersection-like characterization for $\alpha$ statistical compactness has also been established.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:In this research, we present the notion of statistical compactness restricted up to order $\alpha$, where $\alpha \in (0,1]$.
📊
Key Findings & Data:There exist statistically compact spaces that are not compact.
💡
Conclusion & Impact:A finite intersection-like characterization for $\alpha$ statistical compactness has also been established.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Countable compactness · natural density · finite intersection property.
Abstract
In this research, we present the notion of statistical compactness restricted up to order $\alpha$, where $\alpha \in (0,1]$. There exist statistically compact spaces that are not compact. So the parameter $\alpha$ became the measurement of non compactness. Additionally, we looked for the continued existence of order $\alpha$ statistical compactness under open continuous surjection and sub-space topology. A finite intersection-like characterization for $\alpha$ statistical compactness has also been established.
🔖
Cite This Article
Datta, T., Bal, P., Das, P. (2024). Parameterized Statistical Compactness of Topological Spaces. Turkish Journal of Mathematics and Computer Science, Volume: 16 Issue: 2. https://doi.org/10.47000/tjmcs.1542927