An innovative method for enhancing residential load forecasting in the Central Asian region based on a machine learning technique

Key Points

• The research aims to improve residential load forecasting in the Central Asian region using machine learning techniques.
• Develop a novel machine learning model for forecasting residential energy loads.
• Integrate regional energy consumption patterns into the model.
• Evaluate the model's accuracy against traditional forecasting methods.
• The machine learning model demonstrated improved forecasting accuracy compared to conventional techniques.
• Predictions showed reduced error margins, enhancing reliability for energy providers.
• Increased forecasting efficiency may lead to better energy resource management.