| Proj No. | A3017-251 |
| Title | Data-Driven Optimization of District Cooling Efficiency |
| Summary | This project applies machine learning models to forecast district cooling load and energy use. The predictions are tested to improve chiller plant efficiency, aiming to reduce energy consumption (kWh/RT) and support sustainable urban cooling while maintaining comfort. |
| Supervisor | A/P Chau Yuen (Loc:S1 > S1 B1A > S1 B1A 12, Ext: +65 67905420) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Centre for Information Sciences & System (CISS) (Loc: S2-B4b-05) |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: |