Resilience evaluation of multi-feature system based on hidden Markov model

IF 9.4 1区 工程技术 Q1 ENGINEERING, INDUSTRIAL Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI:10.1016/j.ress.2024.110561
Jiaying Liu , Jun Zhang , Qingfeng Tian , Bei Wu
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Abstract

Modern systems have become increasingly vulnerable to threats due to their growing complexity nowadays. Multi-feature systems, prevalent in the realm of complex structures, manifest their performance through a diverse array of features. In response to threats, this paper develops a resilience evaluation model for multi-feature systems based on hidden Markov models, which can describe the dynamic relationship between performance levels and external features. Quantitative resilience indicators are presented across three distinct dimensions: resistant, absorption, and recovery, whose analytical formulas are derived by generating functions and properties are proved. Meanwhile, simulation algorithms are proposed to verify the correctness of the analytic formulas. Finally, taking the system under the threat of flood disasters as an example, the resilience model proposed in this paper is applied to evaluate its resilience, and the robustness of the resilience evaluation indicators is verified.
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基于隐马尔可夫模型的多特征系统复原力评估
由于现代系统日益复杂,它们越来越容易受到威胁。多特征系统是复杂结构领域的普遍现象,通过一系列不同的特征来体现其性能。为应对威胁,本文基于隐马尔可夫模型开发了多特征系统的弹性评估模型,该模型可描述性能水平与外部特征之间的动态关系。该模型可描述性能水平与外部特征之间的动态关系。本文从三个不同的维度提出了定量弹性指标:抵抗、吸收和恢复,并通过生成函数推导出其解析公式,证明了其属性。同时,提出了仿真算法来验证解析公式的正确性。最后,以洪水灾害威胁下的系统为例,应用本文提出的复原力模型对其复原力进行评价,验证了复原力评价指标的稳健性。
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来源期刊
Reliability Engineering & System Safety
Reliability Engineering & System Safety 管理科学-工程:工业
CiteScore
15.20
自引率
39.50%
发文量
621
审稿时长
67 days
期刊介绍: Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.
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