TY - JOUR AB - Purpose This paper aims to explore detection of heating load of building by machine learning. Detection of heating load of building is very important in design of buildings due to efficient energy consumption.Design/methodology/approach In this study, detection of heating load of building based on effects of dry-bulb temperature, dew-point temperature, radiation, diffuse radiation and wind speed was analyzed. Machine learning approach was implemented for such a purpose.Findings The obtained results could be useful for future planning of heating load of buildings. Because the heating load of building is a very nonlinear phenomenon, it is suitable to use machine learning approach to avoid the nonlinearity of the system.Originality/value The obtained results could be used effectively in detection of heating load of buildings. VL - 38 IS - 1 SN - 0260-2288 DO - 10.1108/SR-07-2017-0139 UR - https://doi.org/10.1108/SR-07-2017-0139 AU - Swhli Khaled Mohamed Himair AU - Jovic Srdjan AU - Arsic Nebojša AU - Spalevic Petar PY - 2017 Y1 - 2017/01/01 TI - Detection and evaluation of heating load of building by machine learning T2 - Sensor Review PB - Emerald Publishing Limited SP - 99 EP - 101 Y2 - 2024/03/29 ER -