Prediction of Failures in the Air Pressure System of Scania Trucks Using a Random Forest and Feature Engineering
| Autor: | Christopher Gondek, Oliver R. Sampson, Daniel Hafner |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Truck
Feature engineering Computer science Dimensionality reduction 020208 electrical & electronic engineering Feature extraction ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology computer.software_genre Field (computer science) Random forest Feature (computer vision) Histogram 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining computer |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319463483 IDA |
| DOI: | 10.1007/978-3-319-46349-0_36 |
| Popis: | This paper demonstrates an approach in data analysis to minimize overall maintenance costs for the air pressure system of Scania trucks. Feature creation on histograms was used. Randomly chosen subsets of attributes were then evaluated to generate an order and a final subset of features. Finally, a Random Forest was applied and fine-tuned. The results clearly show that data analysis in the field is beneficial and improves upon the naive approaches of checking every truck or no truck until failure. |
| Databáze: | OpenAIRE |
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