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一种具有应用且在风险分析中具有高于随机阈值的可靠性峰值的新型复合帕累托模型。

A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysis.

作者信息

Abiad Mohammad, El-Raouf M M Abd, Yousof Haitham M, Bakr M E, Samson Balogun Oluwafemi, Yusuf M, Mekiso Getachew Tekle, Tashkandy Yusra A

机构信息

College of Business Administration, American University of the Middle East, Egaila, Kuwait.

Basic and Applied Science Institute, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt.

出版信息

Sci Rep. 2025 Jul 1;15(1):21068. doi: 10.1038/s41598-025-07426-3.

DOI:10.1038/s41598-025-07426-3
PMID:40596497
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12219654/
Abstract

This paper aims to model the bimodal and right-skewed aircraft windshield data using a novel compounded-Pareto distribution. The method of maximum likelihood is employed to estimate the unknown model parameters, and the performance of the estimators under finite samples is evaluated through a comprehensive simulation study. The practical applicability of the proposed model is demonstrated using two real-world reliability datasets. Reliability analysis based on Peaks Over a Random Threshold Value at Risk (PORT-VAR) is crucial for aircraft windshield manufacturers, as it provides a rigorous assessment of extreme failure events and service times-key factors in ensuring product safety and longevity. By identifying the frequency and severity of failures exceeding specific VAR thresholds, this analysis enables companies to understand the upper bounds of their products' performance under stress, optimize designs for enhanced durability, and develop proactive maintenance strategies. In this paper, we present a comprehensive reliability PORT-VAR analysis to support these objectives and highlight the relevance of the proposed model in extreme value risk modeling and real-world reliability scenarios.

摘要

本文旨在使用一种新颖的复合帕累托分布对双峰和右偏态的飞机挡风玻璃数据进行建模。采用最大似然法估计未知模型参数，并通过全面的模拟研究评估有限样本下估计量的性能。使用两个实际可靠性数据集证明了所提出模型的实际适用性。基于风险随机阈值之上的峰值（PORT-VAR）的可靠性分析对飞机挡风玻璃制造商至关重要，因为它提供了对极端故障事件和服务时间的严格评估，而这些是确保产品安全和寿命的关键因素。通过确定超过特定VAR阈值的故障频率和严重程度，该分析使公司能够了解其产品在压力下性能的上限，优化设计以提高耐用性，并制定主动维护策略。在本文中，我们提出了全面的可靠性PORT-VAR分析以支持这些目标，并强调所提出模型在极值风险建模和实际可靠性场景中的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/fc6e869a9a84/41598_2025_7426_Fig19_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/451c433c9be3/41598_2025_7426_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/e705470bfea6/41598_2025_7426_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/b273d84ebb62/41598_2025_7426_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/508ffd52fa90/41598_2025_7426_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/408a7d6684f2/41598_2025_7426_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/968a11c32c6f/41598_2025_7426_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/000585b5f59b/41598_2025_7426_Fig17_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f46/12219654/fc6e869a9a84/41598_2025_7426_Fig19_HTML.jpg

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