使用当代的三角模糊排名方法,对洛马克斯分布进行了增强的参数估计.
D Kalpanapriya1, Pullooru Bhavana1
1Vellore Institute of Technology, India.
MethodsX
|January 13, 2025
概括
这项研究引入了一种新的三角模糊排名方法,用于估计洛马克斯分布参数. 这种方法改善了可靠性和寿命分析中不确定数据的处理.
科学领域:
- 统计 统计 统计 统计
- 可靠性工程可靠性工程
- 模糊的数学 模糊的数学
背景情况:
- 洛马克斯分布对于可靠性和生命周期数据建模至关重要.
- 罗马克斯分布的参数估计面临着不确定或不准确数据的挑战.
- 现有的方法在模糊环境中与不完整的数据集作斗争.
研究的目的:
- 为洛马克斯分布参数估计提出一种新的三角模糊排名方法.
- 在模糊统计分析中增强不完整数据集的处理.
- 提高在不确定性条件下参数估计的可靠性和准确性.
主要方法:
- 为三角模糊数字 (TFN) 开发一个当代的三角模糊排名函数.
- 拟议的排名方法应用于洛马克斯分布参数估计.
- 通过广泛的数值模拟进行验证.
主要成果:
- 拟议的方法显著改善了模糊环境中的洛马克斯分布的参数估计.
- 增强不完整和不确定的数据集的解释和处理.
- 证明了对现有估计技术的稳定性和优势.
结论:
- 新的三角模糊排名方法为洛马克斯分布参数估计提供了更好的方法.
- 这种方法在处理不准确或不完整的数据时提供更可靠的估计.
- 这些发现对在不确定的条件下可靠性分析和生命周期数据建模具有重大意义.
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