Figure 11: Summary of error information of 160 sampled data.
In this study, we decided to address the issue by the filtering off
sampled data which had large relative errors. However, these incoming
with random errors were not known in real-time operation. Therefore, it
requires a way to train the artificial intelligence models to predict
data errors accurately before the data are cleaned. A successful
exercise should lead to an outcome of lower standard deviation of
relative errors.