Forecasting Lightpath Quality of Transmission and Implementing Uncertainty in…
The recent popularity of using deep learning models for the forecasting of time series calls for methods to not only predict the target but also measure the uncertainty of the prediction accurately…
Extraction and Early Detection of Anomalies in Lightpath SNR Using Machine Le…
In a context of ever-increasing traffic, a degradation of the optical layer could affect client demands, in particular the quality of service provided by telecommunications operators. Thus, the rap…
Multivariate Machine Learning Models for Short-Term Forecast of Lightpath Per…
Machine learning (ML) is emerging as a promising solution for managing the physical layer complexity of heterogeneous dynamic optical networks transporting multiple applications in a software defin…
Reinforcement Learning for Compensating Power Excursions in Amplified WDM Sys…
Wavelength-dependent power excursions in gain-controlled erbium doped fiber amplifiers (EDFA) is a challenging issue in optical networks. We investigate a launch channel power control method using …
Trends in Optical Span Loss Detected Using the Time Series Decomposition Method
Optical fiber cables deployed in the last 30 years have been considered to be long-lived components due to the generally high level of reliability of glass and the robustness of cable construction.…
Karya Umum 
Filsafat 
Agama 
Ilmu-ilmu Sosial 
Bahasa 
Ilmu-ilmu Murni 
Ilmu-ilmu Terapan 
Kesenian, Hiburan, dan Olahraga 
Kesusastraan 
Geografi dan Sejarah