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| Deep feature analysis and extraction on Logged Vehicle data for the task of predictive maintenance |
| OneLineSummary | This project is about applying supervised/unsupervised methods of feature selection on Logged Vehicle data (LVD) from Volvo trucks and investigate the contribution in model construction for different predictive maintenance tasks + |
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| Prerequisites | Machine Learning + |
| References | • Doquet, Guillaume, and Michele Sebag. "A … • Doquet, Guillaume, and Michele Sebag. "Agnostic feature selection." The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2019 • Prytz, Rune, et al. "Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data." Engineering applications of artificial intelligence 41 (2015): 139-150.rtificial intelligence 41 (2015): 139-150. |
| StudentProjectStatus | Open + |
| Supervisors | Mahmoud Rahat + , Sławomir Nowaczyk + |
| Title | Deep feature analysis and extraction on Logged Vehicle data for the task of predictive maintenance + |
| Categories | StudentProject + |
| Modification dateThis property is a special property in this wiki. | 14 October 2019 15:06:30 + |
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