Study on network traffic forecast model of SVR optimized by GAFSA

DOI10.1016/j.chaos.2015.10.019zbMath1360.62470OpenAlexW2198869818MaRDI QIDQ528374

Yuan Liu, RuiXue Wang

Publication date: 12 May 2017

Published in: Chaos, Solitons and Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.chaos.2015.10.019

zbMATH Keywords

self-similarityglobal artificial fish swarm algorithm (GAFSA)network traffic forecastoptimization of parameterssupport vector regression (SVR)

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Stochastic network models in operations research (90B15)

Related Items (2)

Dynamics of the congestion control model in underwater wireless sensor networks with time delay ⋮ Long-term forecasting of time series based on linear fuzzy information granules and fuzzy inference system

Uses Software

• LIBSVM

Cites Work

• Maximum likelihood least squares identification for systems with autoregressive moving average noise
• Fractional processes and fractional-order signal processing. Techniques and applications
• Neural network forecasting for seasonal and trend time series

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