New stochastic fractional integral and related inequalities of Jensen-Mercer and Hermite-Hadamard-Mercer type for convex stochastic processes

被引:6
|
作者
Jarad, Fahd [1 ,2 ]
Sahoo, Soubhagya Kumar [3 ]
Nisar, Kottakkaran Sooppy [4 ]
Treanta, Savin [5 ,6 ,7 ]
Emadifar, Homan [8 ]
Botmart, Thongchai [9 ]
机构
[1] Cankaya Univ, Dept Math, TR-06790 Ankara, Turkiye
[2] China Med Univ, China Med Univ Hosp, Taichung 40402, Taiwan
[3] CV Raman Global Univ, Dept Math, Bhubaneswar 752054, Orissa, India
[4] Prince Sattam bin Abdulaziz Univ, Coll Sci & Humanities Alkharj, Dept Math, Wadi Alkharj 11942, Saudi Arabia
[5] Univ Politehn Bucuresti, Dept Appl Math, Bucharest 060042, Romania
[6] Acad Romanian Scientists, 54 Splaiul Independentei, Bucharest 050094, Romania
[7] Univ Politehn Bucuresti, Fundamental Sci Appl Engn Res Ctr SFAI, Bucharest 060042, Romania
[8] Islamic Azad Univ, Dept Math, Hamedan Branch, Hamadan, Iran
[9] Khon Kaen Univ, Fac Sci, Dept Math, Khon Kaen 40002, Thailand
关键词
Convex stochastic process; Hermite-Hadamard-Mercer inequality; Fractional integral operator; Exponential kernel; APPROXIMATIONS;
D O I
10.1186/s13660-023-02944-y
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this investigation, we unfold the Jensen-Mercer (J - M) inequality for convex stochastic processes via a new fractional integral operator. The incorporation of convex stochastic processes, the J - M inequality and a fractional integral operator having an exponential kernel brings a new direction to the theory of inequalities. With this in mind, estimations of Hermite-Hadamard-Mercer (H - H - M)-type fractional inequalities involving convex stochastic processes are presented. In the context of the new fractional integral operator, we also investigate a novel identity for differentiable mappings. Then, a new related H - H - M-type inequality is presented using this identity as an auxiliary result. Applications to special means and matrices are also presented. These findings are particularly appealing from the perspective of optimization, as they provide a larger context to analyze optimization and mathematical programming problems.
引用
收藏
页数:18
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