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Automation of Fast Configuration Error Diagnosis in Optical Transport Networks – Natural Language Processing is All You Need

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Abstract

We train language models to automate the diagnosis of OTN configuration errors, and the diagnostic accuracy is up to 97.56%. We additionally demonstrate the effectiveness of the models on a real OTN system.

© 2023 The Author(s)

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