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Showing papers on "Reliability (statistics) published in 2022"


Journal ArticleDOI
TL;DR: In this paper, a hybrid AI empowered forecasting model that combines singular spectrum analysis (SSA) and parallel long short term memory (PLSTM) neural networks is proposed to predict irregular sudden changes and capture longterm dependencies in the data.

42 citations


Journal ArticleDOI
TL;DR: This study proposes a time-dependent, reliability-based method for the optimal load-dependent sensor placement considering multi-source uncertainties using a non-probabilistic theory to characterize the uncertainty in the uncertainty propagation process for model updating.

39 citations


Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors proposed a novel recommendation method which incorporates temporal reliability and confidence measures into the recommendation process and evaluated the quality of the predictions using a temporal reliability measure taking into account the changes of users' preferences over time.
Abstract: Recommender systems use intelligent algorithms to learn a user’s preferences and provide them relevant suggestions. Lack of sufficient ratings – also known as data sparsity problem – often results in poor recommendation performance. The existing recommendation methods have mainly focused on designing recommenders with high accuracy without paying much attention to the reliability of the recommendations. On the other hand, the users’ preferences may vary over time and considering the time factor in the design process is crucial, which has been largely ignored in most of the existing recommenders. To deal with these issues, a novel recommendation method is proposed in this paper which incorporates temporal reliability and confidence measures into the recommendation process. First, the effectiveness of the users’ rating is measured using a probabilistic approach and ineffective rating profiles are enriched by adding some implicit ratings to them. The quality of the predictions is evaluated using a temporal reliability measure taking into account the changes of users’ preferences over time. Then, the ratings with low reliability values are recalculated using a novel procedure, which updates the target user’s neighborhood by removing ineffective users. This leads to a temporal confidence measure that is used to update the neighborhood to provide more reliable and accurate recommendations. The superiority of the proposed method over state-of-the-art recommendation methods is shown by conducting extensive experiments on three benchmark datasets.

37 citations


Journal ArticleDOI
TL;DR: In this article, a new learning function with a parallel processing strategy is proposed for selecting new training samples for complex systems, which combines dependent Kriging predictions and parallel learning strategy to further improve the computational efficiency.

36 citations


Journal ArticleDOI
TL;DR: A novel reliability model for demand-based warm standby systems with capacity storage is formulating, in which the chronological characteristics of warm standby components are explicitly explored before and after their activation.

30 citations


Journal ArticleDOI
TL;DR: A convolutional neural network (CNN)-based regression approach is proposed to determine the minimum amount of load curtailments of sampled states without solving optimal power flow (OPF) except in the training stage, which is computationally efficient (fast and accurate) in calculating the most common composite system reliability indices.

27 citations


Journal ArticleDOI
TL;DR: In this paper, a hybrid planning of distributed generation and distribution automation in distribution networks aiming to improve the reliability and operation indices is presented, where the objective function minimizes the sum of the expected daily investment, operation, energy loss and reliability costs.

27 citations


Journal ArticleDOI
TL;DR: In this article, the authors investigated how consumers capitalize on online reviews for purchase decisions in three markets (Taiwan, Thailand, and Vietnam) and demonstrated the mediating role of online trust in the online reviews and purchase decision relationship under the moderating effect of perceived effectiveness of social media platforms.

22 citations


Journal ArticleDOI
TL;DR: The solved problems indicate that the proposed AK–SESC approach provides accurate answers with much fewer function calls than SESC and can be a promising method for reliability analyses involving nonlinear or high-dimensional performance functions with small failure probabilities.

20 citations


Journal ArticleDOI
TL;DR: This study investigates the most recent variant of RAP, namely, the RAP with heterogeneous components under the mixed redundancy strategy, and proposes an exact branch-and-price algorithm for the problem that solves in less than one CPU second all the benchmark instances reported in the literature.

19 citations


Journal ArticleDOI
TL;DR: In this article, a new physics-informed meta-learning framework for tool wear prediction under varying wear rates is presented, which employs the empirical equations' parameters to improve the interpretability of the modeling and optimization of the data-driven models.

Journal ArticleDOI
TL;DR: In this paper a security and reliability viewpoint is implemented for the simultaneous transmission expansion planning and the optimal placement of battery storage systems.

Journal ArticleDOI
TL;DR: This framework includes guidance on the characterisation of a mixture of uncertainties, efficient methodologies to integrate data into design decisions, and to conduct reliability analysis, and risk/reliability based design optimisation.

Journal ArticleDOI
TL;DR: In this article, the individual difference and measurement error are considered in the estimation of the mean function in the Wiener process for degradation modeling and estimating reliability, which can improve the reliability and lifetime estimation accuracies.

Journal ArticleDOI
TL;DR: In this article, a reliability model for systems subject to multiple dependent competing failure processes affected by Markovian environments is proposed, where the effect of dynamic environment is embodied in that the natural wear behavior of the system in different environments is controlled by distinct gamma processes.

Journal ArticleDOI
TL;DR: Results demonstrate that the proposed AL-DLGPR-PDEM achieves a fair tradeoff between accuracy and efficiency for dealing with high-dimensional reliability problems in both static and dynamic analysis examples.

Journal ArticleDOI
Chen Zequan1, Guofa Li1, Jialong He1, Zhaojun Yang1, Jili Wang1 
TL;DR: RBIK strives to rapidly enable the Kriging model to satisfy the GCC rather than focusing on a single candidate sample, which is the most obvious difference between RBIK and other adaptive structural reliability analysis methods.

Journal ArticleDOI
TL;DR: In this article, a Bayesian network probabilistic framework is suggested for reliability prediction of two conceptual subsea processing systems and a suitable reliability prediction method for mechanical equipment is selected and illustrated stepwise to estimate the total failure rate of the main subsea equipment from reliability data available for similar offshore topside equipment.

Journal ArticleDOI
TL;DR: In this article, a Gamma-based stochastic resistance degradation model is developed by incorporating the spatial degradation into a non-stationary degradation process, and based on the hazard-function-based reliability analysis method, a novel reliability assessment approach of aging structures is proposed.

Journal ArticleDOI
TL;DR: In this paper, a direct probability integral method (DPIM) is proposed to uniformly attack system reliability problems of static and dynamic structures, and the role of smoothing of Dirac delta function in DPIM for stochastic response and reliability analyses is revealed.


Journal ArticleDOI
TL;DR: This research investigates the use of output-only structural health monitoring (SHM) to evaluate the reliability and safety of highway steel plate girders of WonHyo bridge and shows the effectiveness of PARIMA for detecting structures damages and analyzing structure’s reliability in semi-static and dynamic domains.

Journal ArticleDOI
TL;DR: The method proposed in this paper can be used to evaluate the reliability of the anti-loosening performance of bolted joints comprehensively and accurately.

Journal ArticleDOI
TL;DR: In this paper, the adaptive multi-fidelity Gaussian process for reliability analysis (AMGPRA) is proposed to find the optimal training point and information source simultaneously using the novel collective learning function (CLF ).

Journal ArticleDOI
TL;DR: An integrated reliability evaluation method is proposed based on the pseudo-sequential Monte Carlo simulation that can improve the economic efficiency of distribution systems while enhancing the power supply capacity.

Journal ArticleDOI
01 Jan 2022
TL;DR: In this article, an adaptive Monte-Carlo sampling approach is proposed to estimate the probability of line overflow in a high voltage direct current power transmission grid with linear reliability constraints on power injections and line currents.
Abstract: Electricity production currently generates approximately 25% of greenhouse gas emissions in the USA. Thus, increasing the amount of renewable energy is a key step to carbon neutrality. However, integrating a large amount of fluctuating renewable generation is a significant challenge for power grid operating and planning. Grid reliability, i.e., an ability to meet operational constraints under power fluctuations, is probably the most important of them. In this letter, we propose computationally efficient and accurate methods to estimate the probability of line overflow, i.e., reliability constraints violation, under a known distribution of renewable energy generation. To this end, we investigate an importance sampling approach, a flexible extension of Monte-Carlo methods, which adaptively changes the sampling distribution to generate more samples near the reliability boundary. The approach allows to estimate overload probability in real-time based only on a few dozens of random samples, compared to thousands required by the plain Monte-Carlo. Our study focuses on high voltage direct current power transmission grids with linear reliability constraints on power injections and line currents. We propose a novel theoretically justified physics-informed adaptive importance sampling algorithm and compare its performance to state-of-the-art methods on multiple IEEE power grid test cases.

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper presented a long shortterm memory (LSTM)-augmented deep learning framework for time-dependent reliability analysis of dynamic systems, where multiple LSTMs were trained to generate local surrogate models of dynamic system in the time-independent system input space.

Journal ArticleDOI
TL;DR: In this article, the authors investigated the potential role of grid-connected battery swapping station (BSS) with vehicle-to-grid (V2G) in improving the economy and reliability of the distribution system.

Journal ArticleDOI
TL;DR: The high predicted accuracy demonstrates that the reliability of oil condition prediction can be guaranteed even with small samples, and the proposed data augmentation method is proposed for improved prediction by integrating degradation mechanisms and monitoring data.

Journal ArticleDOI
TL;DR: In this paper, the authors evaluated the reliability of pressure vessels made of composite materials (carbon and glass fiber) with respect to stress and burst pressure and found that the relationship between deterministic safety coefficients and reliability is highly non-linear and the reliability properties of the composite materials are similar to those made of steel or aluminum alloy.