Evolutionary Machine Learning-Based Energy Consumption Prediction for the industry

In the digitalization of industry and 4.0 environment, it is important to master accurate forecasting energy demand in order guarantee continuity production service as well improve reliability electrical system while promoting efficiency strategies industrial sector. This paper proposes machine learning models predict consumption an plant, which takes into account at-tributes that directly consumption. The proposed this work include Multiple Linear Regression (MLR), Decision Tree (DT), Recurrent Neural Networks (RNN) Gated United (GRU), are compared according their performances criteria help find best models. Basing on simulation results, proven MLR approach method.