Creating a Dataset Used for Applying Machine Learning Techniques to Accurately Forecast the Energy Cost in Home-Based Small Businesses

A systematic approach to creating datasets for applying machine learning techniques to forecast the energy cost in home-based small businesses accurately remains a primary requirement in this practice. However, a ready-to-use dataset remains a significant challenge when performing energy cost forecasting in home-based small businesses. Unfortunately, much research has not been conducted to address this issue directly despite its recurrence in real-world applications. The CRMDV approach proposed in this study is designed to provide a framework for creating a ready-to-use time series dataset that can be leveraged via machine learning techniques to forecast the energy cost in home-based small businesses accurately.