Machine learning models for forecasting municipal solid waste generation: a case study of Malaysia

Key Points

• Forecasting municipal solid waste generation shows significant accuracy using machine learning methods, indicating promising results.
• Key evidence indicates that machine learning models achieved an accuracy of over 85% in predicting waste generation volumes.
• Analysis utilizing various machine learning algorithms demonstrates effective predictions based on municipal data patterns.
• Findings suggest that integrating machine learning in waste management could lead to more efficient strategies and reduced environmental impact.