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In a system, there are identical replaceable components working for a given task and a failed component is replaced by a functioning one in the corresponding position, which characterizes a repairable system. Assuming that a replaced…

This paper develops maintenance policies for a system under condition monitoring. We assume that a number of defects may develop and the degradation process of each defect follows a gamma process, respectively. The system is inspected…

Systems and Control · Electrical Eng. & Systems 2024-09-21 Shaomin Wu , Inma T. Castro

We introduce the exchangeable rewiring process for modeling time-varying networks. The process fulfills fundamental mathematical and statistical properties and can be easily constructed from the novel operation of random rewiring. We derive…

Statistics Theory · Mathematics 2015-07-29 Harry Crane

A new class of probabilistic models for cascading failure propagation in interconnected systems is proposed. The models take into account important characteristics of real systems that are not considered in existing generic approaches.…

Disordered Systems and Neural Networks · Physics 2010-03-31 Jörg Lehmann , Jakob Bernasconi

This review article provides an overview of recent work in the modeling and analysis of recurrent events arising in engineering, reliability, public health, biomedicine and other areas. Recurrent event modeling possesses unique facets…

Methodology · Statistics 2007-08-03 Edsel A. Peña

In this paper, a production model based on (hyperbolic) differential equations with stochastic and load-dependent machine failures is introduced. We derive the model on the base of a well-established deterministic model and show its…

Probability · Mathematics 2019-12-13 Simone Göttlich , Stephan Knapp

Motivated by queueing applications, we study various reflected autoregressive processes with dependencies. Amongst others, we study cases where the interarrival and service times are proportionally dependent with additive and/or subtracting…

Probability · Mathematics 2023-10-03 Ioannis Dimitriou , Dieter Fiems

We investigate how to model exchangeability with choice functions. Exchangeability is a structural assessment on a sequence of uncertain variables. We show how such assessments are a special indifference assessment, and how that leads to a…

Artificial Intelligence · Computer Science 2017-03-07 Arthur Van Camp , Gert de Cooman

Dependability is an umbrella concept that subsumes many key properties about a system, including reliability, maintainability, safety, availability, confidentiality, and integrity. Various dependability modeling techniques have been…

Software Engineering · Computer Science 2016-06-23 Waqar Ahmed , Osman Hasan , Sofiene Tahar

This paper studies distribution-free inference in settings where the data set has a hierarchical structure -- for example, groups of observations, or repeated measurements. In such settings, standard notions of exchangeability may not hold.…

Statistics Theory · Mathematics 2025-08-05 Yonghoon Lee , Rina Foygel Barber , Rebecca Willett

The article is focused on studying how to predict the failure times of coherent systems from the early failure times of their components. Both the cases of independent and dependent components are considered by assuming that they are…

Applications · Statistics 2024-09-30 Jorge Navarro , Antonio Arriaza , Alfonso Suárez-Llorens

In this paper, a new reliability model has been developed for a single system degrading stochastically which experiences soft and hard failure. Soft failure occurs when the physical deterioration level of the system is greater than a…

Statistics Theory · Mathematics 2019-03-04 Nooshin Yousefi , David W. Coit

We argue for supplementing the process of training a prediction algorithm by setting up a scheme for detecting the moment when the distribution of the data changes and the algorithm needs to be retrained. Our proposed schemes are based on…

Machine Learning · Computer Science 2021-02-23 Vladimir Vovk , Ivan Petej , Ilia Nouretdinov , Ernst Ahlberg , Lars Carlsson , Alex Gammerman

Data-driven modeling and machine learning are widely used to model the behavior of dynamic systems. One application is the residual evaluation of technical systems where model predictions are compared with measurement data to create…

Machine Learning · Computer Science 2023-05-09 Arman Mohammadi , Theodor Westny , Daniel Jung , Mattias Krysander

The ongoing evolution of the electric power systems brings about the need to cope with increasingly complex interactions of technical components and relevant actors. In order to integrate a more comprehensive spectrum of different aspects…

Systems and Control · Computer Science 2013-08-21 Markus Schläpfer , Tom Kessler , Wolfgang Kröger

The reliability of processes with moving elastic and isotropic material containing initial cracks is considered in terms of fracture. The material is modelled as a moving plate which is simply supported from two of its sides and subjected…

Computational Engineering, Finance, and Science · Computer Science 2016-04-25 Maria Tirronen

Producing probabilistic forecasts for large collections of similar and/or dependent time series is a practically relevant and challenging task. Classical time series models fail to capture complex patterns in the data, and multivariate…

Machine Learning · Statistics 2019-05-30 Yuyang Wang , Alex Smola , Danielle C. Maddix , Jan Gasthaus , Dean Foster , Tim Januschowski

In this paper, a repairable multi-component system is studied where all the components can be repaired individually within the system. The whole system is inspected at inspection intervals and the failed components are detected and replaced…

Signal Processing · Electrical Eng. & Systems 2020-02-04 Nooshin Yousefi , David W. Coit , Zhu Xiaoyan

In large distributed systems, failures are a daily event occurring frequently, especially with growing numbers of computation tasks and locations on which they are deployed. The advantage of representing an application with a workflow is…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-09 Alberto Mulone , Doriana Medić , Marco Aldinucci

When analyzing data from multiple sources, it is often convenient to strike a careful balance between two goals: capturing the heterogeneity of the samples and sharing information across them. We introduce a novel framework to model a…

Methodology · Statistics 2026-03-02 Laura D'Angelo , Bernardo Nipoti , Andrea Ongaro