Artificial neural networks in applying MCUSUM residuals charts for AR(1) processes

@article{Arkat2007ArtificialNN,
  title={Artificial neural networks in applying MCUSUM residuals charts for AR(1) processes},
  author={Jamal Arkat and Seyed Taghi Akhavan Niaki and Babak Abbasi},
  journal={Applied Mathematics and Computation},
  year={2007},
  volume={189},
  pages={1889-1901}
}
The usual key assumptions in designing quality control charts are the normality and independency of serial samples. While the normality assumption holds in most cases, in many continuous-flow processes such as the chemical processes, serial samples have some degrees of autocorrelation associated with them. Ignoring the autocorrelation structure in constructing control charts, results in decreasing the in-control run length, and so increasing the false alarms. Moreover, when the object is to… CONTINUE READING

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