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.