Applications of AI for Predictive Maitenance

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F23%3A10252584" target="_blank" >RIV/61989100:27740/23:10252584 - isvavai.cz</a>

Result on the web

<a href="https://events.it4i.cz/event/158/" target="_blank" >https://events.it4i.cz/event/158/</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Applications of AI for Predictive Maitenance

Original language description

Using machine or deep learning to predict specific imminent events can be useful for many applications, like predicting the failure of a hard disk or unexpected downtime of a compute node. Such events can be considered anomalies that occur unexpectedly and rarely. Hence, it is a challenge to train machine and deep learning models for these due to lack of appropriate training data.This course covered three different methods, using XGBoost, Long Short-Term Memory (LSTM), and Autoencoders. For each, detailed hands-on exercises were provided to learn how to use these methods and how to select and pre-process training data for them.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/MC2301" target="_blank" >MC2301: National Competence Centres in the framework of EuroHPC Phase 2 - EUROCC 2</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů