Real-time Flood Overflow Forecasting In Urban Drainage Systems By Using Time-series Multi-stacking Of Data Mining Techniques

This study introduces a novel multi-stacking model that integrates different decision tree frameworks to forecast water levels in urban drainage systems (UDS). This model blends different data mining techniques for predictions with different timesteps, and is expected to improve the accuracy of overflow forecasting in early warning systems.