Results 91 to 100 of about 420,626 (277)
The Sequential Normal Scores Transformation
, 2017 The sequential analysis of series often requires nonparametric procedures, where the most powerful ones frequently use rank transformations. Re-ranking the data sequence after each new observation can become too intensive computationally. This led to the
Conover, W. J. +2 more
core +1 more source
A control chart for monitoring image processes based on convolutional neural networks
Statistica Neerlandica, Volume 79, Issue 1, February 2025.In this paper, the problem of monitoring image processes with spatially correlated pixels over time is considered. An exponentially weighted moving average (EWMA) control chart for monitoring such processes based on a convolutional neural network (CNN) is proposed.
Yarema Okhrin +2 more
wiley +1 more source
Loss-Based Control Charts for Monitoring Non-Normal Process Data
IEEE Access, 2020 Quality and loss of products are crucial factors in competitive companies, and firms widely adopt a loss function to measure the loss caused by a deviation in the quality variable from the target value.
Su-Fen Yang, Lijuan Shen
doaj +1 more source
An improved adaptive EWMA control chart for monitoring time between events with application in health sector [PDF]
, 2023 Muhammad Aslam +4 more
openalex +1 more source
IET Blockchain, Volume 5, Issue 1, January/December 2025.This study proposes a blockchain‐driven framework for monitoring and governing cryptocurrency ‘tax‐base dark matter’. By integrating a consortium chain, rule‐guided transaction graph analysis, tax‐semantic zero‐knowledge proofs, dynamic‐weight consensus and privacy‐preserving KYC decoupling, the model balances compliance, privacy and cross‐border ...
Yisheng Lin
wiley +1 more source
An Examination of the Robustness to Non Normality of the EWMA Control Charts for the Dispersion [PDF]
The EWMA control chart is used to detect small shifts in a process. It has been shown that, for certain values of the smoothing parameter, the EWMA chart for the mean is robust to non normality.
Maravelakis, Petros +2 more
core +1 more source
IET Generation, Transmission &Distribution, Volume 19, Issue 1, January/December 2025.This paper proposes a robust, user‐type‐specific anomaly detection method for electricity usage. First, after data cleaning and preprocessing, a correntropy‐based K‐means clustering method is proposed to perform robust clustering, effectively separating users with non‐Gaussian noisy data.
Teng Zhang +4 more
wiley +1 more source
Designing an efficient adaptive EWMA model for normal process with engineering applications
Ain Shams Engineering JournalStability in process parameters is required to ensure the quality of the finished item. Control charts, as one of the critical parts of statistical process monitoring (SPM), have seen widespread use across many disciplines for detecting and responding to
Zahid Rasheed +5 more
doaj +1 more source
EWMA Chart and Measurement Error [PDF]
Measurement error is a usually met distortion factor in real-world applications that influences the outcome of a process. In this paper, we examine the effect of measurement error on the ability of the EWMA control chart to detect out-of-control ...
Maravelakis, Petros +2 more
core +1 more source
A Two‐Stage Model for Outlier Detection and Power Prediction of Wind Turbine Using SCADA Dataset
International Journal of Energy Research, Volume 2025, Issue 1, 2025.As wind energy adoption grows, ensuring reliable power generation becomes critical. However, its inherent variability, caused by fluctuations in wind speed, direction, and environmental conditions, poses challenges for grid integration and operational planning.
Fatma Mazen Ali Mazen +3 more
wiley +1 more source