703 - 710 |
A neuro-fuzzy model for prediction of the indoor temperature in typical Australian residential buildings Alasha'ary H, Moghtaderi B, Page A, Sugo H |
711 - 720 |
Energy-saving potential by improving occupants' behavior in urban residential sector in Hangzhou City, China Ouyang JL, Hokao K |
721 - 731 |
Durability of 20-year-old external insulation and assessment of various types of retrofitting to meet new energy regulations Stazi F, Di Perna C, Munafo P |
732 - 737 |
Development and experimental validation of a high-temperature heat pump for heat recovery and building heating Wang K, Cao F, Xing ZW |
738 - 744 |
Study of ventilation cooling technology for telecommunication base stations in Guangzhou Chen Y, Zhang YF, Meng QL |
745 - 752 |
Heat fluxes through roofs and their relevance to estimates of urban heat storage Meyn SK, Oke TR |
753 - 768 |
Constructing load profiles for household electricity and hot water from time-use data-Modelling approach and validation Widen J, Lundh M, Vassileva I, Dahlquist E, Ellegard K, Wackelgard E |
769 - 773 |
Numerical study on the heat storing capacity of concrete walls with air cavities Zhang ZL, Wachenfeldt BJ |
774 - 780 |
Application of multicriteria analysis in designing HVAC systems Avgelis A, Papadopoulos AM |
781 - 789 |
Domestic lighting: A high-resolution energy demand model Richardson I, Thomson M, Infield D, Delahunty A |
790 - 800 |
Application of energy rating methods to the existing building stock: Analysis of some residential buildings in Turin Ballarini I, Corrado V |
801 - 808 |
Sensitivity of the total heat loss coefficient determined by the energy signature approach to different time periods and gained energy Sjogren JU, Andersson S, Olofsson T |