MULTIVARIATE CUSUM CONTROL CHART BASED ON THE RESIDUALS OF MULTIOUTPUT LEAST SQUARES SVR FOR MONITORING WATER QUALITY

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Hidayatul Khusna
Muhammad Mashuri
Suhartono S.
Dedy Dwi Prastyo
Muhammad Ahsan

Abstract

Monitoring serially dependent processes using conventional control charts yields a high false alarm rate. Multioutput Least Squares Support Vector Regression (MLS-SVR) has the capability to encompass the cross-relatedness between output variables by learning multivariate output variables simultaneously. This research aims to develop a Multivariate Cumulative Sum (MCUSUM) control chart based on the residual obtained from the MLS-SVR model for monitoring autocorrelated data. The inputs of the MLS-SVR are selected using the significant lag of a partial autocorrelation function. The proposed control chart is applied to monitor water quality data and it can detect the assignable causes in those data caused by a broken pipeline.

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How to Cite
Khusna, H., Mashuri, M., S., S., Prastyo, D. D., & Ahsan, M. (2019). MULTIVARIATE CUSUM CONTROL CHART BASED ON THE RESIDUALS OF MULTIOUTPUT LEAST SQUARES SVR FOR MONITORING WATER QUALITY. Malaysian Journal of Science, 38(Sp2), 73–83. https://doi.org/10.22452/mjs.sp2019no2.7
Section
ISMI-ICTAS18 (Published)

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