An overview on application of machine learning techniques in optical networks

F Musumeci, C Rottondi, A Nag… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …

Resource assignment based on dynamic fuzzy clustering in elastic optical networks with multi-core fibers

H Yang, Q Yao, A Yu, Y Lee… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Space-division multiplexing elastic optical networks (SDM-EONs) will play an important role
in addressing the increasing Internet traffic, thanks to their spectrum utilization flexibility and …

Unified monitoring and telemetry platform supporting network intelligence in optical networks

S Shen, J Han, K Bardhi, H Li, R Yang… - Journal of Optical …, 2025 - opg.optica.org
In recent years, machine-learning (ML) applications have<? TeX 2pc 0pt?> generated
considerable interest and shown great potential in optimizing optical network management …

A semi-quantitative information based fault diagnosis method for the running gears system of high-speed trains

C Cheng, X Qiao, H Luo, W Teng, M Gao… - IEEE …, 2019 - ieeexplore.ieee.org
The proper operation of running gears of a high-speed train is one of the key factors to
ensure its safety and reliability. The diagnosis of the state of running gears of a high-speed …

LSTM for cloud data centers resource allocation in software-defined optical networks

M Aibin - 2020 11th IEEE Annual Ubiquitous Computing …, 2020 - ieeexplore.ieee.org
Nowadays, artificial intelligence provides an excellent opportunity for scientists to improve
the efficiency of resource allocation in communication networks. In this paper, we focus on …

Analysis of OSNR and Data Rate Selection Using ML Techniques for Optical Networks

S Vishwakarma, RK Jeyachitra - 2020 5th International …, 2020 - ieeexplore.ieee.org
Optical networks are preferred over other wireless network in modern world due to better link
quality in long haul networks. The basic parameters that define any optical network is Quality …

Multiple multidimensional fuzzy reasoning algorithm based on neural network

Z Zhao, G Ni, Y Shen, N Hassan - Journal of Intelligent & …, 2018 - content.iospress.com
In the past, intelligent system often realized reasoning operation by interpolation method for
one-dimensional sparse rule base, and could not analyze fuzzy reasoning of multi …

Machine Learning Application in the Hybrid Optical Wireless Networks

D Naik, T De - Machine Intelligence and Soft Computing: Proceedings …, 2021 - Springer
Complex problems invariably involve big data. Machine learning (ML) deals with this big
data. Machine learning does classification, regression and decision making better than …

Amplifier control using machine learning and coloured optical packet switching node design in optical networks

MJF Hermelo - 2020 - theses.hal.science
Data rate and energy consumption are the major concerns in optical networks. In order to
reduce energy consumption, transport operator networks based on optical circuit switching …

Optical amplifier cognitive gain adjustment methodology for dynamic and realistic networks

UC de Moura, M Garrich, AC Cesar, JD Reis… - Cognitive …, 2017 - Springer
Optical amplifiers are essential devices in optical networks to recover the signals degraded
from passive optical components attenuations such as fiber span and optical switches …