Identification and prediction of discrete chaotic maps applying a Chebyshev neural network

DOI10.1016/S0960-0779(98)00302-6zbMath1115.68469OpenAlexW2003545651MaRDI QIDQ997487

P. Akritas, Valery V. Ivanov, Ioannis E. Antoniou

Publication date: 6 August 2007

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

Full work available at URL: https://doi.org/10.1016/s0960-0779(98)00302-6

zbMATH Keywords

multi-layer perceptron

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

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Robustness of LSTM neural networks for multi-step forecasting of chaotic time series ⋮ Comparison of different chaotic maps in particle swarm optimization algorithm for long-term cascaded hydroelectric system scheduling ⋮ Shifted-Chebyshev-polynomial-based numerical algorithm for fractional order polymer visco-elastic rotating beam ⋮ Multi-step ahead nonlinear identification of Lorenz's chaotic system using radial basis neural network with learning by clustering and particle swarm optimization ⋮ Fuzzy prediction of chaotic time series based on fuzzy clustering ⋮ An efficient entire chaos-based scheme for deniable authentication ⋮ Nonlinear analysis of network traffic

Cites Work

• Chaos, fractals, and noise: Stochastic aspects of dynamics.
• A method for approximating one-dimensional functions
• Perspectives of Nonlinear Dynamics
• Solving nonlinear recursions
• Learning representations by back-propagating errors
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