Energy Pattern Classification and Prediction in an Educational Institution using Deep Learning Framework
Author:
Affiliation:
1. Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai, Tamil Nādu, India
Funder
Science and Engineering Research Board
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Energy Engineering and Power Technology
Link
https://www.tandfonline.com/doi/pdf/10.1080/15325008.2022.2139432
Reference27 articles.
1. A. Blázquez-García, A. Conde, U. Mori and J. A. Lozano, “A review on outlier/anomaly detection in time series data,” ACM Comput. Surveys (CSUR), vol. 54, no. 3, pp. 1–33, 2021.
2. Modelling energy demand from higher education institutions: A case study of the UK
3. Building power consumption datasets: Survey, taxonomy and future directions
4. A Prediction Methodology of Energy Consumption Based on Deep Extreme Learning Machine and Comparative Analysis in Residential Buildings
5. Machine learning for energy consumption prediction and scheduling in smart buildings
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