Cross-feature trained machine learning models for QoT-estimation in optical networks
Author:
Affiliation:
1. National University of Sciences and Technology, Islamabad
2. DET, Politecnico di Torino, Corso Duca degli Abruzzi, Turin
Publisher
SPIE-Intl Soc Optical Eng
Subject
General Engineering,Atomic and Molecular Physics, and Optics
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Forecasting Lightpath Quality of Transmission and Implementing Uncertainty in the Forecast Models;Journal of Lightwave Technology;2023-08-01
2. Knowledge Distillation-Based Compression Model for QoT Estimation of an Unestablished Lightpaths;2023 23rd International Conference on Transparent Optical Networks (ICTON);2023-07-02
3. Machine Learning Techniques in Optical Networks: A Systematic Mapping Study;IEEE Access;2023
4. Query Based Iterative Learning Approach for Lightpath Deployment in Optical Networks;2022 Asia Communications and Photonics Conference (ACP);2022-11-05
5. Performance Analysis of Transfer-learning Approaches for QoT Estimation of Network Operating with 400ZR;2022 Asia Communications and Photonics Conference (ACP);2022-11-05
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