*2.4. Model Selection Criteria*

All statistical forecasting methods could be used to fit a model on a dataset. However, it is difficult to fit a model that captures all the variabilities in a demand load dataset, considering the numerous complex factors that influence demand load forecasting. Additionally, obtaining accurate demand load forecasts based only on parameters such as weather information and other factors that influence consumption may not always be correct since, under certain circumstances, some predictive models have higher prediction accuracy than others. Hence, the criteria for selecting the best fit model under certain conditions is critical for accurate demand load forecasting. Given this, various methods are proposed in this framework to address these challenges, as mentioned earlier.
