Robust online detection in serially correlated directed network

نویسندگان

چکیده

As the complexity of production processes increases, diversity data types drives development network monitoring technology. This paper mainly focuses on an online algorithm to detect serially correlated directed networks robustly and sensitively. First, we consider a transition probability matrix resolve double correlation primary data. Further, since sum each row is one, it standardizes data, facilitating subsequent modeling. Then extend spring length based method multivariate case propose adaptive cumulative (CUSUM) control chart strength weighted statistic monitor networks. novel approach assumes only that process observation associated with nearby points without any parametric time series model, which in line reality. Simulation results real example from metro transportation demonstrate superiority our design.

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ژورنال

عنوان ژورنال: Naval Research Logistics

سال: 2023

ISSN: ['1520-6750', '0894-069X']

DOI: https://doi.org/10.1002/nav.22128