Title of article :
Predicting of infected People with Corona virus (covid-19) by using Non-Parametric Quality Control Charts
Author/Authors :
Mostafa Fawzy, Heba Department of statistics - college of administration and Economics - University of Baghdad, Iraq , Ghalib, Asmaa Department of statistics - college of administration and Economics - University of Baghdad, Iraq
Pages :
12
From page :
2115
To page :
2126
Abstract :
Quality control Charts were used to monitor the number of infections with the emerging corona virus (Covid-19) for the purpose of predicting the extent of the disease's control, knowing the extent of its spread, and determining the injuries if they were within or outside the limits of the control charts. The research aims to use each of the control chart of the (Kernel Principal Component Analysis Control Chart) and (K- Nearest Neighbor Control Chart). As (18) variables representing the governorates of Iraq were used, depending on the daily epidemiological position of the Public Health Department of the Iraqi Ministry of Health. To compare the performance of the charts, a measure of average length of run was adopted, as the results showed that the number of infection with the new Corona virus is out of control, and that the (KNN) chart had better performance in the short term with a relative equality in the performance of the two charts in the medium and long rang
Keywords :
Quality Control Control Charts , Average Length of Range , Nearest Neighborhood , Kernel Principal Components Analysis
Journal title :
International Journal of Nonlinear Analysis and Applications
Serial Year :
2022
Record number :
2713002
Link To Document :
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