TY - CHAP
T1 - Machine learning for building energy forecasting
AU - Seyedzadeh, Saleh
AU - Pour Rahimian, Farzad
PY - 2021/1/16
Y1 - 2021/1/16
N2 - In recent years, Artificial Intelligence (AI) in general and Machine Learning (ML) techniques in specific terms have been proposed for forecasting of building energy consumption and performance. This chapter provides a substantial review on the four main ML approaches including artificial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance.
AB - In recent years, Artificial Intelligence (AI) in general and Machine Learning (ML) techniques in specific terms have been proposed for forecasting of building energy consumption and performance. This chapter provides a substantial review on the four main ML approaches including artificial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance.
KW - building energy forecasting
KW - building energy analysis
KW - building energy consumption
UR - http://www.scopus.com/inward/record.url?scp=85101078415&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-64751-3_4
DO - 10.1007/978-3-030-64751-3_4
M3 - Chapter
AN - SCOPUS:85101078415
SN - 978-3-030-64750-6
T3 - Green Energy and Technology
SP - 41
EP - 76
BT - Data-Driven Modelling of Non-Domestic Buildings Energy Performance
PB - Springer
CY - Cham, Switzerland
ER -