A data-driven approach is proposed to accurately predict individualized thermal comfort conditions by integrating the ASHRAE Global Thermal Comfort Database II with subject-based thermal comfort profiles of building occupants. By applying transfer learning techniques, this framework generates subject-specific models that enhance accuracy despite limited data points. Combinatorial probability analysis indicates that achieving total satisfaction becomes […]
