Enhancing energy savings verification in industrial settings using deep learning and anomaly detection within the IPMVP framework

Enhancing energy savings verification in industrial settings using deep learning and anomaly detection within the IPMVP framework

This study advances industrial energy Measurement and Verification (M&V) practices by integrating Deep Learning (DL) techniques with automated anomaly detection, challenging traditional M&V reliance on manual non-routine adjustments. The research explores whether automated, data-driven anoma...

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Bibliographic Details
Main Authors: Sukarti, Suziee, Sulaima, Mohamad Fani, Abdul Kadir, Aida Fazliana, Zulkafli, Nur Izyan, Othman, Mohammad Lutfi, Hanak, Dawid P.
Format: Article
Language:English
Published: Elsevier Ltd 2025
Online Access:http://psasir.upm.edu.my/id/eprint/120176/
http://psasir.upm.edu.my/id/eprint/120176/1/120176.pdf

Internet

http://psasir.upm.edu.my/id/eprint/120176/
http://psasir.upm.edu.my/id/eprint/120176/1/120176.pdf

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