Integrating machine learning with metaheuristic optimization for power consumption prediction

Key Points

• Power consumption predictions improved significantly by integrating machine learning with metaheuristic optimization strategies,
• The study showed a notable accuracy increase of 25% in predictive models, highlighting the potential for better energy management.
• Analysis of algorithms revealed that combining metaheuristic techniques with machine learning enhances forecast precision in real-time environments.
• These findings emphasize the need for integrating advanced predictive tools, suggesting a shift towards energy-efficient practices.