Learning from data: Applications of Machine Learning in optical network design and modeling

被引:0
|
作者
Alberto Hernandez, Jose [1 ]
机构
[1] Univ Carlos III Madrid, Dept Ingn Telemat, Getafe, Spain
基金
欧盟地平线“2020”;
关键词
Machine Learning; Communication Networks; Simulated data; Passive Optical Networks; Routing and Wavelength Allocation; IPACT; CAPACITY; PON;
D O I
暂无
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This article overviews the uses and applications of classical Machine Learning techniques in a variety of network problems. We first overview the basics of statistical learning, including the main algorithms and methodologies involved in the process of designing good Machine Learning models. The second part addresses a number of network use cases where ML can be used to complement and extend existing network models and algorithms, including the classical Routing and Wavelength Assignment (RWA) problem and fiber access delay modelling.
引用
收藏
页数:6
相关论文
共 50 条
  • [2] Comprehensive overview of machine learning applications in MOFs: from modeling processes to latest applications and design classifications
    Liu, Yutong
    Dong, Yawen
    Wu, Hua
    JOURNAL OF MATERIALS CHEMISTRY A, 2025, 13 (04) : 2403 - 2440
  • [3] Machine Learning Applications in Optical Networks
    Tornatore, Massimo
    2019 24TH OPTOELECTRONICS AND COMMUNICATIONS CONFERENCE (OECC) AND 2019 INTERNATIONAL CONFERENCE ON PHOTONICS IN SWITCHING AND COMPUTING (PSC), 2019,
  • [4] Special Issue "Statistical Data Modeling and Machine Learning with Applications II"
    Gocheva-Ilieva, Snezhana
    Ivanov, Atanas
    Kulina, Hristina
    MATHEMATICS, 2023, 11 (12)
  • [5] Data Augmentation to Improve Machine Learning for Optical Network Failure Management
    Khan, Lareb Zar
    Pedro, Joao
    Costa, Nelson
    Napoli, Antonio
    Sambo, Nicola
    2022 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC), 2022,
  • [6] Design patterns for Machine Learning Applications
    Sharma, Ruchi
    Davuluri, Kiran
    PROCEEDINGS OF THE 2019 3RD INTERNATIONAL CONFERENCE ON COMPUTING METHODOLOGIES AND COMMUNICATION (ICCMC 2019), 2019, : 818 - 821
  • [7] Decoding Optical Data with Machine Learning
    Fang, Jie
    Swain, Anand
    Unni, Rohit
    Zheng, Yuebing
    LASER & PHOTONICS REVIEWS, 2021, 15 (02)
  • [8] Machine learning and deep learning methods for wireless network applications
    Abel C. H. Chen
    Wen-Kang Jia
    Feng-Jang Hwang
    Genggeng Liu
    Fangying Song
    Lianrong Pu
    EURASIP Journal on Wireless Communications and Networking, 2022
  • [9] Machine learning and deep learning methods for wireless network applications
    Chen, Abel C. H.
    Jia, Wen-Kang
    Hwang, Feng-Jang
    Liu, Genggeng
    Song, Fangying
    Pu, Lianrong
    EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2022, 2022 (01)
  • [10] Drug design by machine learning: Ensemble learning for QSAR modeling
    Liu, Y
    ICMLA 2005: FOURTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS, 2005, : 187 - 193