Browsing Statistics (Scholarly Publications) by Author "Zhang, Mimi"
Now showing items 1-18 of 18
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An Ameliorated Improvement Factor Model for Imperfect Maintenance and Its Goodness of Fit
Zhang, Mimi; Xie, Min (2017)Maintenance actions can be classified, according to their efficiency, into three categories: perfect maintenance, imperfect maintenance, and minimal maintenance. To date, the literature on imperfect maintenance is voluminous, ... -
A Bivariate Maintenance Policy for Multi-State Repairable Systems with Monotone Process
Zhang, Mimi; Xie, Min; Gaudoin, Olivier (2013)In this paper, a sequential failure limit maintenance policy for a repairable system is studied. The system is assumed to have states, including one working state and failure states, and the multiple failure states are ... -
A Condition-Based Maintenance Strategy for Heterogeneous Populations
Zhang, Mimi; Ye, Zhisheng; Xie, Min (2014)This paper develops a maintenance strategy, called inspection-replacement policy, to cope with heterogeneous populations. Burn-in is the procedure by which most of the defective products in a heterogeneous population can ... -
Continuous-Observation Partially Observable Semi-Markov Decision Processes for Machine Maintenance
Zhang, Mimi; Revie, Matthew (2017)Partially observable semi-Markov decision processes (POSMDPs) provide a rich framework for planning under both state transition uncertainty and observation uncertainty. In this paper, we widen the literature on POSMDP by ... -
DCF: An Efficient and Robust Density-Based Clustering Method
Zhang, Mimi (2021)Density-based clustering methods have been shown to achieve promising results in modern data mining applications. A recent approach, Density Peaks Clustering (DPC), detects modes as points with high density and large ... -
Degradation-Based Maintenance Using Stochastic Filtering for Systems under Imperfect Maintenance
Zhang, Mimi; Xie, Min; Gaudoin, Olivier (2015)The stationaryWiener process is widely used in modeling degradation processes, mainly due to the existence of an analytical expression of the first hitting time distribution. However, it is only appropriate for modelling ... -
Forward-Stagewise Clustering: An Algorithm for Convex Clustering
Zhang, Mimi (2019)This paper proposes an exceptionally simple algorithm, called forward-stagewise clustering, for convex clustering. Convex clustering has drawn recent attention since it nicely addresses the instability issue of traditional ... -
A Heuristic Policy for Maintaining Multiple Multi-State Systems
Zhang, Mimi (2020)This work is concerned with the optimal allocation of limited maintenance resources among a collection of competing multi-state systems, and the dynamic of each multi-state system is modelled by a Markov chain. Determining ... -
Incorporating Ignorance within Game Theory: An Imprecise Probability Approach
Zhang, Mimi (2023)Ignorance within non-cooperative games, reflected as a player’s uncertain prefer- ences towards a game’s outcome, is examined from a Bayesian point of view. This topic has had scarce treatment in the literature, which ... -
Learning Mixtures of Gaussian Processes through Random Projection
Zhang, Mimi (2024)We propose an ensemble clustering framework to uncover latent cluster labels in functional data generated from a Gaussian process mixture. Our method exploits the fact that the projection coefficients of the functional ... -
Lower Confidence Limit for Reliability Based on Grouped Data with a Quantile Filling Algorithm
Zhang, Mimi; Hu, Qingpei; Xie, Min; Yu, Dan (2014)The purpose of this article is to derive a lower confidence limit for reliability given a grouped data set. This is done by using a quantile filling algorithm which generates pseudo failure data from grouped data. A general ... -
Model selection with application to gamma process and inverse Gaussian process
Zhang, Mimi (2016)The gamma process and the inverse Gaussian process are widely used in condition-based maintenance. Both are suitable for modelling monotonically increasing degradation processes. Hence, one challenge for practitioners ... -
Reinforced EM Algorithm for Clustering with Gaussian Mixture Models
Zhang, Mimi (2023)Methods that employ the EM algorithm for parameter estimation typically face the notorious yet unsolved problem that the initialization input significantly impacts the algorithm output. We here develop a Reinforced ... -
Saddlepoint Approximation for the Generalized Inverse Gaussian Levy Process
Zhang, Mimi (2022)The generalized inverse Gaussian (GIG) Lévy process is a limit of compound Poisson processes, including the stationary gamma process and the stationary inverse Gaussian process as special cases. However, fitting the GIG ... -
A Stochastic EM Algorithm for Progressively Censored Data Analysis
Zhang, Mimi; Ye, Zhi-Sheng; Xie, Min (2014)Progressive censoring technique is useful in lifetime data analysis. Simple approaches to progressive data analysis are crucial for its widespread adoption by reliability engineers. This study develops an efficient yet ... -
A Theoretical Analysis of Density Peaks Clustering and the Component-wise Peak-Finding Algorithm
Zhang, Mimi (2024)Density peaks clustering detects modes as points with high density and large distance to points of higher density. Each non-mode point is assigned to the same cluster as its nearest neighbor of higher density. Density ... -
Vine Copula Approximation: A Generic Method for Coping with Conditional Dependence
Zhang, Mimi; Bedford, Tim (2018)Pair-copula constructions (or vine copulas) are structured, in the layout of vines, with bivariate copulas and conditional bivariate copulas. The main contribution of the current work is an approach to the long-standing ... -
Weighted Clustering Ensemble: A Review
Zhang, Mimi (2022)Clustering ensemble has emerged as a powerful tool for improving both the robustness and the stability of results from individual clustering methods. Weighted clustering ensemble arises naturally from clustering ensemble. ...