| 1 |
Evaluation of thermal comfort in an office building served by a liquid desiccant-assisted evaporative cooling air-conditioning system
Cho HJ, Jeong JW
Energy and Buildings, 172, 361, 2018 |
| 2 |
Operation planning method for home air-conditioners considering characteristics of installation environment
Kuroha R, Fujimoto Y, Hirohashi W, Amano Y, Tanabe S, Hayashi Y
Energy and Buildings, 177, 351, 2018 |
| 3 |
Adaptive thermal comfort in the different buildings of Darjeeling Hills in eastern India - Effect of difference in elevation
Thapa S, Bansal AK, Panda GK, Indraganti M
Energy and Buildings, 173, 649, 2018 |
| 4 |
PMV-based event-triggered mechanism for building energy management under uncertainties
Xu ZB, Hu GQ, Spanos CJ, Schiavon S
Energy and Buildings, 152, 73, 2017 |
| 5 |
Balancing indoor thermal comfort and energy consumption of ACMV systems via sparse swarm algorithms in optimizations
Zhai DQ, Soh YC
Energy and Buildings, 149, 1, 2017 |
| 6 |
Evaluation of thermal comfort in a test room equipped with a photovoltaic assisted thermo-electric air duct cooling system
Irshad K, Habib K, Kareem MW, Basrawi F, Saha BB
International Journal of Hydrogen Energy, 42(43), 26956, 2017 |
| 7 |
Potential of artificial neural networks to predict thermal sensation votes
von Grabe J
Applied Energy, 161, 412, 2016 |
| 8 |
Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation
Chen X, Wang Q, Srebric J
Applied Energy, 164, 341, 2016 |
| 9 |
The IMBPC HVAC system: A complete MBPC solution for existing HVAC systems
Ruano AE, Pesteh S, Silva S, Duarte H, Mestre G, Ferreira PM, Khosravani HR, Horta R
Energy and Buildings, 120, 145, 2016 |
| 10 |
Development of the adaptive PMV model for improving prediction performances
Kim JT, Lim JH, Cho SH, Yun GY
Energy and Buildings, 98, 100, 2015 |
