Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > ACPC > 2018 > Su3E > Su3E.4
  • Asia Communications and Photonics Conference (ACP) 2018
  • OSA Technical Digest (Optica Publishing Group, 2018),
  • paper Su3E.4

Which Features Most Impact: Prediction of ANN-Based Lightpath Quality of Transmission?

Longfei Li, Gangxiang Shen, Xiaodong Fu, Shuiping Jie, and Sanjay Kumar Bose

Not Accessible

Your library or personal account may give you access

Abstract

Artificial neural networks (ANN) have been widely employed for predicting quality of transmission (QoT) of lightpaths, in which different features play different roles. This study aims to find the features that most impact the lightpath QoT. The evaluation shows that the total length of a lightpath is the one that most impacts the lightpath QoT.

© 2018 The Author(s)

PDF Article
More Like This
QoT estimation for Unestablished Lightpaths Using Artificial Neural Networks

Min Zhang, Dong Fu, Bo Xu, Baojian Wu, and Kun Qiu
JTu2A.32 CLEO: Applications and Technology (CLEO:A&T) 2018

ANN-Based Transfer Learning for QoT Prediction in Real-Time Mixed Line-Rate Systems

Weiyang Mo, Yue-Kai Huang, Shaoliang Zhang, Ezra Ip, Daniel C. Kilper, Yoshiaki Aono, and Tsutomu Tajima
W4F.3 Optical Fiber Communication Conference (OFC) 2018

986 km Field Trial of Cascaded ANN-based Link-Penalty Models for QoT Prediction

R. Yang, S. Shen, H. Li, Z. Shi, R. Wang, R. Nejabati, S. Yan, and D. Simeonidou
W4G.5 Optical Fiber Communication Conference (OFC) 2023

View More...
Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use