Data-driven predictive models for daily electricity consumption of academic buildings

Data-driven predictive models for daily electricity consumption of academic buildings

Academic buildings in a typical university campus occupy 42% of the total space and are responsible for nearly 50 percent of the total energy use and carbon emissions of the campus. Forecasting of energy consumption in this energy intensive building category could help higher education institutions...

Full description

Bibliographic Details
Main Authors: Bilal Akbar, Khuram Pervez Amber, Anila Kousar, Muhammad Waqar Aslam, Muhammad Anser Bashir, Muhammad Sajid Khan
Format: Article
Language:English
Published: AIMS Press 2020-12-01
Series:AIMS Energy
Subjects:
data-driven forecasting models
electricity consumption
academic buildings
ann
Online Access:http://awstest.aimspress.com/article/doi/10.3934/energy.2020.5.783?viewType=HTML

Internet

http://awstest.aimspress.com/article/doi/10.3934/energy.2020.5.783?viewType=HTML

Similar Items