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Cited by

• 2003Statistical Surveillance. Optimality and Methods156 cited
• 1995A multi-layer neural network model for detecting changes in the process mean145 cited
• 2010Application of statistical process control charts to monitor changes in animal production systems1106 cited
• 2003Surveillance of a Simple Linear Regression37 cited
• 2005Real-time pattern recognition in statistical process control: A hybrid neural network/decision tree-based approach33 cited
• 2004OPTIMIZING FEEDFORWARD NEURAL NETWORKS FOR CONTROL CHART PATTERN RECOGNITION THROUGH GENETIC ALGORITHMS31 cited
• 1999Detecting When a Monotonically Increasing Mean Has Crossed a Threshold31 cited
• 2015Robust Tukey–CUSUM Control Chart for Process Monitoring25 cited
• 2008Using an MQE chart based on a self-organizing map NN to monitor out-of-control signals in manufacturing processes22 cited
• 2021An adaptive CUSUM chart for drift detection20 cited
• 2005Detection of linear trends in process mean16 cited
• 1996Algorithm AS 305: Average Run Lengths for Cumulative Sum Control Charts Under Linear Trend10 cited
• 2011Bayesian estimation of the time of a linear trend in risk-adjusted control charts9 cited
• 2013A Hybrid Learning-Based Model for Simultaneous Monitoring of Process Mean and Variance