✨
AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
The results presented here extend, generalize, and integrate many previous results in the literature.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:In this article, we will determine the best proximity point results for the Geraghty proximal contraction type mappings in a more general space called the bv(s)-metric space, and prove the existence of the best proximity point for such mappings which satisfy the RJ-Property.
📊
Key Findings & Data:We also derive some consequences as a justification for the validity of the main result.
💡
Conclusion & Impact:The results presented here extend, generalize, and integrate many previous results in the literature.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:best proximity point · Geraghty proximal contraction · RJ-Property
Abstract
In this article, we will determine the best proximity point results for the Geraghty proximal contraction type mappings in a more general space called the bv(s)-metric space, and prove the existence of the best proximity point for such mappings which satisfy the RJ-Property. We also derive some consequences as a justification for the validity of the main result. The results presented here extend, generalize, and integrate many previous results in the literature.
🔖
Cite This Article
Kumssa, L. B. (2022). GERAGHTY PROXIMAL CONTRACTION TYPE MAPPINGS AND RJ-PROPERTY IN bv(s) -METRIC SPACES. Results in Nonlinear Analysis, 2022 - Cilt 5, Sayı 4, 487–498. https://doi.org/10.53006/rna.1065458