no code implementations • 19 Apr 2022 • Deqing Zhai, Yeng Chai Soh
In this study, a novel application of neural networks that predict thermal comfort states of occupants is proposed with accuracy over 95%, and two optimization algorithms are proposed and evaluated under two real cases (general offices and lecture theatres/conference rooms scenarios) in Singapore.
no code implementations • 20 Jul 2016 • Chaoyang Jiang, Mustafa K. Masood, Yeng Chai Soh, Hua Li
The accuracy is up to 94 percent with a tolerance of four occupants.
