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Fractional $ 3/8 $-Simpson type inequalities for differentiable convex functions

  • Received: 10 December 2023 Revised: 22 January 2024 Accepted: 23 January 2024 Published: 26 January 2024
  • MSC : 26A51, 26D10, 26D15

  • The main objective of this study is to establish error estimates of the new parameterized quadrature rule similar to and covering the second Simpson formula. To do this, we start by introducing a new parameterized identity involving the right and left Riemann-Liouville integral operators. On the basis of this identity, we establish some fractional Simpson-type inequalities for functions whose absolute value of the first derivatives are s-convex in the second sense. Also, we examine the special cases $ m = 1/2 $ and $ m = 3/8 $, as well as the two cases $ s = 1 $ and $ \alpha = 1 $, which respectively represent the classical convexity and the classical integration. By applying the definition of convexity, we derive larger estimates that only used the extreme points. Finally, we provide applications to quadrature formulas, special means, and random variables.

    Citation: Nassima Nasri, Badreddine Meftah, Abdelkader Moumen, Hicham Saber. Fractional $ 3/8 $-Simpson type inequalities for differentiable convex functions[J]. AIMS Mathematics, 2024, 9(3): 5349-5375. doi: 10.3934/math.2024258

    Related Papers:

  • The main objective of this study is to establish error estimates of the new parameterized quadrature rule similar to and covering the second Simpson formula. To do this, we start by introducing a new parameterized identity involving the right and left Riemann-Liouville integral operators. On the basis of this identity, we establish some fractional Simpson-type inequalities for functions whose absolute value of the first derivatives are s-convex in the second sense. Also, we examine the special cases $ m = 1/2 $ and $ m = 3/8 $, as well as the two cases $ s = 1 $ and $ \alpha = 1 $, which respectively represent the classical convexity and the classical integration. By applying the definition of convexity, we derive larger estimates that only used the extreme points. Finally, we provide applications to quadrature formulas, special means, and random variables.



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