PredMaX: Predictive maintenance with explainable deep convolutional autoencoders

Author:

Hajgató GergelyORCID,Wéber Richárd,Szilágyi Botond,Tóthpál Balázs,Gyires-Tóth Bálint,Hős Csaba

Funder

Nemzeti Kutatási, Fejlesztési és Innovaciós Alap

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems,Building and Construction

Reference49 articles.

1. A systematic literature review of machine learning methods applied to predictive maintenance;Carvalho;Comput. Ind. Eng.,2019

2. Predictive maintenance in the industry 4.0: A systematic literature review;Zonta;Comput. Ind. Eng.,2020

3. Physically interpretable neural networks for the geosciences: Applications to earth system variability;Toms;J. Adv. Modelling Earth Syst.,2020

4. PlayMolecule glimpse: Understanding protein–ligand property predictions with interpretable neural networks;Varela-Rial;J. Chem. Inform. Model.,2022

5. VisioRed: A visualisation tool for interpretable predictive maintenance;Paraschos,2021

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