Anomaly Detection of Consumption in Hotel Units: A Case Study Comparing Isolation Forest and Variational Autoencoder Algorithms

Anomaly Detection of Consumption in Hotel Units: A Case Study Comparing Isolation Forest and Variational Autoencoder Algorithms

Buildings are responsible for a high percentage of global energy consumption, and thus, the improvement of their efficiency can positively impact not only the costs to the companies they house, but also at a global level. One way to reduce that impact is to constantly monitor the consumption levels...

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Bibliographic Details
Main Authors: Tomás Mendes, Pedro J. S. Cardoso, Jânio Monteiro, João Raposo
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Applied Sciences
Subjects:
outliers detection
data quality
machine learning
deep learning
energy/water/gas anomalous consumption
buildings anomalous consumption detection platform
Online Access:https://www.mdpi.com/2076-3417/13/1/314

Internet

https://www.mdpi.com/2076-3417/13/1/314

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