Machine Learning and Data Segmentation for Building Energy Use Prediction—A Comparative Study
Advances in metering technologies and emerging energy forecast strategies provide opportunities and challenges for predicting both short and long-term building energy usage. Machine learning is an important energy prediction technique, and is significantly gaining research attention. The use of diff...
Main Authors: | William Mounter, Chris Ogwumike, Huda Dawood, Nashwan Dawood |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-09-01
|
Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/14/18/5947 |
Similar Items
-
Wind speed prediction over Malaysia using various machine learning models: potential renewable energy source
by: Marwah Sattar Hanoon, et al.
Published: (2022-12-01) -
House price prediction modeling using machine learning techniques: a comparative study
by: Ayten Yağmur, et al.
Published: (2023-02-01) -
Estimation of calendar age based on autonomic cardiovascular function by applying machine learning techniques
by: Sabeghi Rassoul, et al.
Published: (2021-10-01) -
Fitting segmented polynomial regression models whose join points have to be estimated /
by: 456723 Gallant, A. R., et al. -
Support Vector Regression Method for Predicting Off-Grid Photovoltaic Output Power in the Short Term
by: Kharisma Bani Adam, et al.
Published: (2022-08-01)