乐胖代购免代理版

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Currently, most AI-based prognostics and health management in the automotive industry ignore textual descriptions of the experienced problems or symptoms. With this study, however, we propose an ML-assisted workflow for automotive fault nowcasting that improves on current industry standards. We show that a multilingual pre-trained Transformer model can effectively classify the textual symptom claims from a large company with vehicle fleets, despite the task\u2019s challenging nature due to the 38 languages and 1357 classes involved. 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The class labels, however, are encoded and any released models classify indices and not class names.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical consideration"}}]}}