决策理论在广义阿波罗尼奥斯型二次函数方程近似中的应用

IF 1.5 3区 数学 Q1 MATHEMATICS Journal of Inequalities and Applications Pub Date : 2024-02-20 DOI:10.1186/s13660-024-03103-7
Azam Ahadi, Reza Saadati, Tofigh Allahviranloo, Donal O’Regan
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引用次数: 0

摘要

为了更好地做出近似决策,我们可能需要增加有关近似不同方面的可靠而有用的信息。为了提高阿波罗尼乌斯型二次函数方程近似解的质量和确定性,我们需要测量近似解的质量和确定性以及最大误差。要衡量其质量,我们使用模糊集;要实现其确定性,我们使用概率分布函数。为了提出上述问题,我们应用了 Z 数的概念,并引入了一个形式为 $\mathrm{diag}(A, B, C)$ 的特殊矩阵(命名为广义 Z 数),其中 A 是一个模糊时间戳集合,B 是概率分布函数,C 是 A 的可靠度,用 $A\ast B$ 的值来描述。利用广义 Z 数,我们定义了一种新的控制函数来研究 H-U-R 稳定性,以逼近阿波罗尼奥斯型二次函数方程的解,并保证逼近的质量和确定性。
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An application of decision theory on the approximation of a generalized Apollonius-type quadratic functional equation
To make better decisions on approximation, we may need to increase reliable and useful information on different aspects of approximation. To enhance information about the quality and certainty of approximating the solution of an Apollonius-type quadratic functional equation, we need to measure both the quality and the certainty of the approximation and the maximum errors. To measure the quality of it, we use fuzzy sets, and to achieve its certainty, we use the probability distribution function. To formulate the above problem, we apply the concept of Z-numbers and introduce a special matrix of the form $\mathrm{diag}(A, B, C)$ (named the generalized Z-number) where A is a fuzzy time-stamped set, B is the probability distribution function, and C is a degree of reliability of A that is described as a value of $A\ast B$ . Using generalized Z-numbers, we define a novel control function to investigate H–U–R stability to approximate the solution of an Apollonius-type quadratic functional equation with quality and certainty of the approximation.
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来源期刊
自引率
6.20%
发文量
136
期刊介绍: The aim of this journal is to provide a multi-disciplinary forum of discussion in mathematics and its applications in which the essentiality of inequalities is highlighted. This Journal accepts high quality articles containing original research results and survey articles of exceptional merit. Subject matters should be strongly related to inequalities, such as, but not restricted to, the following: inequalities in analysis, inequalities in approximation theory, inequalities in combinatorics, inequalities in economics, inequalities in geometry, inequalities in mechanics, inequalities in optimization, inequalities in stochastic analysis and applications.
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