Detecting and estimating the time of a single-step change in nonlinear profiles using artificial neural networks

Ali Ghazizadeh, Mehrdad Sarani (), Mahdi Hamid and Ahmad Ghasemkhani
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Ali Ghazizadeh: Sharif University of Technology
Mehrdad Sarani: Iran University of Science and Technology
Mahdi Hamid: University of Tehran
Ahmad Ghasemkhani: University of Tehran

International Journal of System Assurance Engineering and Management, 2023, vol. 14, issue 1, No 7, 74-86

Abstract: Abstract This effort attempts to study the change point problem in the area of non-linear profiles. A method based on Artificial Neural Networks (ANN) is proposed for estimating the real time of a single step change. The feature vector of the proposed Multi-Layer Perceptron (MLP) is based on Z and control chart statistics for nonlinear profiles. The merits of the proposed estimator are evaluated through simulation experiments. The results show that the estimator provides an accurate estimate of the single step change point in non-linear profiles in the selected case problem.

Keywords: Statistical process control; Non-linear profile; Step change point; Artificial Neural Network; Multi-layer perceptron (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13198-021-01121-y

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