The article presents a new method for predicting energy consumption patterns more accurately by considering the relationships between different types of energy. By using Support Vector Regression machines, the researchers developed models that take into account these connections between multiple time series data. The experiments conducted on energy consumption in coking processes showed that the new models outperformed existing methods in forecasting energy usage.