Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)

Explainability and Transparency of Classifiers for Air-Handling Unit Faults Using Explainable Artificial Intelligence (XAI)

In recent years, explainable artificial intelligence (XAI) techniques have been developed to improve the explainability, trust and transparency of machine learning models. This work presents a method that explains the outputs of an air-handling unit (AHU) faults classifier using a modified XAI techn...

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Bibliographic Details
Main Authors: Molika Meas, Ram Machlev, Ahmet Kose, Aleksei Tepljakov, Lauri Loo, Yoash Levron, Eduard Petlenkov, Juri Belikov
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Sensors
Subjects:
buildings
HVAC
fault detection and diagnosis
machine learning
explainable artificial intelligence
XAI
Online Access:https://www.mdpi.com/1424-8220/22/17/6338

Internet

https://www.mdpi.com/1424-8220/22/17/6338

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