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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Furthermore, we provide several remarks to elucidate the connections between our findings and previously established results in the literature.
📌 3 Key Takeaways
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Objective & Hypothesis:In this study, we introduce a novel definition of convexity in the context of exponential coordinates.
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Key Findings & Data:Utilizing this new framework, we establish a series of fractional Hermite-Hadamard type inequalities.
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Conclusion & Impact:Furthermore, we provide several remarks to elucidate the connections between our findings and previously established results in the literature.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Convex functions · co-ordinated convex mapping · Hermite-Hadamard inequality
Abstract
In this study, we introduce a novel definition of convexity in the context of exponential coordinates. Utilizing this new framework, we establish a series of fractional Hermite-Hadamard type inequalities. Furthermore, we provide several remarks to elucidate the connections between our findings and previously established results in the literature.
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Cite This Article
Yılmaz, A., Akkurt, A., Yıldırım, H. (2026). Fractional Integral Inequalities of Hermite–Hadamard type for Exponentially Co-ordinated Convex Functions. Turkish Journal of Mathematics and Computer Science, Volume: 18 Issue: 1. https://doi.org/10.47000/tjmcs.1791073