Abstract
We implement an LSTM-based algorithm to predict and analyse transmission performance and detect anomalies. Cross-validation of the model over two experimental datasets shows high precision of up to 96% for R2 to predict short-term variations.
Original language | English |
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Title of host publication | 2023 Optical Fiber Communications Conference and Exhibition, OFC 2023 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Number of pages | 3 |
ISBN (Electronic) | 9781957171180 |
ISBN (Print) | 9798350312294 |
DOIs | |
Publication status | Published - 19 May 2023 |
Event | The Optical Fiber Communications Conference And Exhibition - OFC 2023 - San Diego, United States Duration: 5 Mar 2023 → 9 Mar 2023 |
Publication series
Name | 2023 Optical Fiber Communications Conference and Exhibition, OFC 2023 - Proceedings |
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Conference
Conference | The Optical Fiber Communications Conference And Exhibition - OFC 2023 |
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Country/Territory | United States |
City | San Diego |
Period | 5/03/23 → 9/03/23 |
Bibliographical note
Publisher Copyright:© 2023 The Author(s).