Yeng Chai Soh
- Comparing occupancy models and data mining approaches for regular occupancy prediction in commercial buildings. Dans: Journal of Building Performance Simulation, v. 10, n. 5-6 (octobre 2017). (2017):
- HVAC system optimization—in-building section. Dans: Energy and Buildings, v. 37, n. 1 (janvier 2005). (2005):
- Modeling regular occupancy in commercial buildings using stochastic models. Dans: Energy and Buildings, v. 103 (septembre 2015). (2015):
- Indoor occupancy estimation from carbon dioxide concentration. Dans: Energy and Buildings, v. 131 (novembre 2016). (2016):
- A fusion framework for occupancy estimation in office buildings based on environmental sensor data. Dans: Energy and Buildings, v. 133 (décembre 2016). (2016):
- Occupancy estimation with environmental sensing via non-iterative LRF feature learning in time and frequency domains. Dans: Energy and Buildings, v. 141 (avril 2017). (2017):
- Balancing indoor thermal comfort and energy consumption of ACMV systems via sparse swarm algorithms in optimizations. Dans: Energy and Buildings, v. 149 (août 2017). (2017):
- Two-stage indoor physical field reconstruction from sparse sensor observations. Dans: Energy and Buildings, v. 151 (septembre 2017). (2017):
- Thermal comfort prediction using normalized skin temperature in a uniform built environment. Dans: Energy and Buildings, v. 159 (janvier 2018). (2018):
- A novel feature selection framework with Hybrid Feature-Scaled Extreme Learning Machine (HFS-ELM) for indoor occupancy estimation. Dans: Energy and Buildings, v. 158 (janvier 2018). (2018):
- Random forest based thermal comfort prediction from gender-specific physiological parameters using wearable sensing technology. Dans: Energy and Buildings, v. 166 (mai 2018). (2018):
- Bayesian filtering for building occupancy estimation from carbon dioxide concentration. Dans: Energy and Buildings, v. 206 (janvier 2020). (2020):
- Machine learning driven personal comfort prediction by wearable sensing of pulse rate and skin temperature. Dans: Building and Environment, v. 170 (mars 2020). (2020):
- Modeling and optimization of different sparse Augmented Firefly Algorithms for ACMV systems under two case studies. Dans: Building and Environment, v. 125 (novembre 2017). (2017):
- CFD results calibration from sparse sensor observations with a case study for indoor thermal map. Dans: Building and Environment, v. 117 (mai 2017). (2017):
- Optimal control of seismically-excited building structures. Dans: Computers & Structures, v. 74, n. 5 (février 2000). (2000):