Some applications on s-logarithmic convex functions are introduced in this study. s-logarithmic convex functions are used to model risk-averse preferences in economics and finance. They play a role in optimization problems, particularly in nonlinear programming and convex optimization functions. Besides, they are encountered in information theory, machine learning, finance and risk management. These applications highlight importance of s-logarithmic convex functions in various domains, where their mathematical properties are strengthen to model complex phenomena and solve practical problems. s-logarithmic convex functions are particularly useful in numerical integration due to their smooth and well-behaved nature. This study focuses on the role of s-logarithmic functions in determining the upper limit for error in numerical integration. The smoothness and well-behaved derivatives of s-logarithmic convex functions facilitate error analysis in numerical integration.
The authors would like to thank Prof. Dr. Ali Mutlu for his contributions to the editing of the article.
| Primary Language | English |
|---|---|
| Subjects | Artificial Intelligence (Other) |
| Journal Section | Research Article |
| Authors | |
| Submission Date | August 5, 2024 |
| Acceptance Date | November 8, 2024 |
| Publication Date | July 3, 2025 |
| DOI | https://doi.org/10.53508/ijiam.1521759 |
| IZ | https://izlik.org/JA65UZ68ED |
| Published in Issue | Year 2025 Volume: 8 Issue: 1 |
International Journal of Informatics and Applied Mathematics