Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction

• Main Authors: Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen
• Format: Article
• Language: English; English
• Published: IEEE 2021
• Subjects: QA Mathematics; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: https://eprints.ums.edu.my/id/eprint/30049/2/Optimal%20variational%20mode%20decomposition%20and%20integrated%20extreme%20learning%20machine%20for%20network%20traffic%20prediction-Abstract.pdf; https://eprints.ums.edu.my/id/eprint/30049/1/Optimal%20variational%20mode%20decomposition%20and%20integrated%20extreme%20learning%20machine%20for%20network%20traffic%20prediction.pdf; https://eprints.ums.edu.my/id/eprint/30049/; https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9388647; https://doi.org/10.1109/ACCESS.2021.3069280
• Institution: Universiti Malaysia Sabah

Network traffic prediction plays a vital role in effective network management, load evaluation and security warning. Extreme learning machine has the advantages of fast convergence speed and strong generalization ability. Also, it does not easily fall into local optima. The evolutionary algorithm ca...