Reliability analysis of high-speed railway network

Gu, Shuang; Li, Keping

doi:10.1177/1748006x19853681

Cited by 11 publications

(8 citation statements)

References 31 publications

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“…Konstantin et al used Markov chain Monte Carlo method to propose a stochastic framework for quantitative assessment of network reliability [15]. Gu et al constructed a topological networked model to study and analyze the reliability of high-speed railway network based on the theory of complex network [16]. In [17], Du et al used important measure for networks to calculate the reliability importance of edges, which can serve as a useful tool to identify component criticality with respect to the system reliability and operational safety.…”

Section: Introductionmentioning

confidence: 99%

Dynamic survivability in oscillator systems

Sun

Wang

2022

Preprint

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Whether the dynamic systems can display normal performance or complete key mission is the hot spot in recent years. In accordance with this, dynamic survivability is defined for the first time and mission-completion-probability is given as an index in this study. Taking the behavior of globally and diffusively coupled oscillator systems with ER and BA network structures as examples, we show the network structures, systems’ parameters and attack strategies exhibit a profound influence on the dynamic survivability. ER and BA systems display better or worse dynamic survivability under different attack strategies respectively. Our outcomes fill the gap in the survivability study and are helpful for enhancing the dynamic survivability of systems.

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Section: Introductionmentioning

confidence: 99%

Dynamic survivability in oscillator systems

Sun

Wang

2022

Preprint

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“…On the other hand, the components that form the similar local topological structures commonly exist in complex network systems. 5 Thus, when analyzing the performances of components and networks, repeated computations are probably performed, 6 increasing the computational burden and hardness of the network analysis. 7–9…”

Section: Introduction and Related Workmentioning

confidence: 99%

Exploiting structural similarity in network reliability analysis using graph learning

Zhang

Xie

Zhu

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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Considering the large-scale networks that can represent construction of components in a unit, a transportation system, a supply chain, a social network system, and so on, some nodes have similar topological structures and thus play similar roles in the network and system analysis, usually complicating the analysis and resulting in considerable duplicated computations. In this paper, we present a graph learning approach to define and identify structural similarity between the nodes in a network or the components in a network system. Based on the structural similarity, we investigate component clustering at various significance levels that represent different extents of similarity. We further specify a spectral-graph-wavelet based graph learning method to measure the structural similarity and present its application in easing computation load of evaluating system survival signature and system reliability. The numerical examples and the application show the insights of structural similarity and effectiveness of the graph learning approach. Finally, we discuss potential applications of the graph-learning based structural similarity and conclude that the proposed structural similarity, component clustering, and graph learning approach are effective in simplifying the complexity of the network systems and reducing the computational cost for complex network analysis.

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“…4,5 Travel agencies, thus, require an exact and efficient approach to assess the performance of their tourism transport networks. Robustness, 6 vulnerability and resilience, [7][8][9] and reliability 10,11 are three main categories investigated recently. Especially, reliability that reflects the network's ability to remain operational under any given circumstances is an increasingly widespread performance indicator.…”

Section: Introductionmentioning

confidence: 99%

Assess reliability of a tourism transport network considering limited-budget and late arrivals

Nguyen

Lin

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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Tourism transport is becoming a crucial part of the tourism industry. Determining the reliability of tourism transport networks is required by travel agencies and other practitioners. However, much of recent reliability assessments cannot utilize directly for tourism transport networks. Moreover, there exists a lack of passengers-oriented reliability evaluation that involves the impacts of latency. Therefore, this study assesses reliability regarding carrying the required number of passengers to their destination under budget and time constraints when considering late arrivals. For reliability assessment, an algorithm, which combines the concept of the minimal path adding a searching procedure with the Recursive Sum of Disjoint Products method, is proposed. An illustrative example is adopted to provide travel agencies with an intuitive visualization of the proposed algorithm. Reliability analysis suggests improving the performance of tourism transport networks.

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Reliability analysis of high-speed railway network

Cited by 11 publications

References 31 publications

Dynamic survivability in oscillator systems

Dynamic survivability in oscillator systems

Exploiting structural similarity in network reliability analysis using graph learning

Assess reliability of a tourism transport network considering limited-budget and late arrivals

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