Forecasting appliances failures: a machine-learning approach to predictive maintenance
Heating appliances consume approximately 48% of the energy spent on household appliances every year. Furthermore, a malfunctioning device can increase the cost even further. Thus, there is a need to create methods that can identify the equipment’s malfunctions and eventual failures before they occur...
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| Outros Autores: | , , , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2020
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10773/28657 |
| País: | Portugal |
| Oai: | oai:ria.ua.pt:10773/28657 |