| KEYWORD |
Machine learning for predictive maintenance
keywords CELLULAR NETWORKS, SMART GRIDS
Reference persons MARCO MELLIA, MICHELA MEO
Research Groups ICT4SS - ICT FOR SMART SOCIETIES, SmartData@PoliTO, Telecommunication Networks Group
Description The topic of the thesis is predictive maintenance of electricity distribution networks through machine learning approaches. The topic is very timely and challenging.
The thesis consists in the analysis of large sets of data about faults, failures and critical events of several elements of an electricity distribution network.
After characterizing events, elements and their behavior, some techniques for identifying and predicting critical events will be studied and proposed.
Required skills The thesis requires skills of data analysis and statistics. Domain knowledge on electricity distribution is also useful.
The work will be developed in a team; hence, team working is expected.
Deadline 09/05/2020
PROPONI LA TUA CANDIDATURA