Chaotic Time Series Prediction Using Rough-Neural Networks

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
‎Artificial neural networks with amazing properties‎, ‎such as universal approximation‎, ‎have been utilized to approximate the nonlinear processes in many fields of applied sciences‎. ‎This work proposes the rough-neural networks (R-NNs) for the one-step ahead prediction of chaotic time series‎. ‎We adjust the parameters of R-NNs using a continuous-time Lyapunov-based training algorithm‎, ‎and prove its stability using the continuous form of Lyapunov stability theory‎. ‎Then‎, ‎we utilize the R-NNs to predict the well-known Mackey-Glass time series‎, ‎and Henon map‎, ‎and compare the simulation results with some well-known neural models‎.
Language:
English
Published:
Mathematics Interdisciplinary Research, Volume:8 Issue: 2, Spring 2023
Pages:
71 to 92
https://www.magiran.com/p2616498  
سامانه نویسندگان
  • Ahmadi، Ghasem
    Corresponding Author (1)
    Ahmadi, Ghasem
    Assistant Professor Mathematics, Payame Noor University, تهران, Iran
  • Dehghandar، Mohammad
    Author (2)
    Dehghandar, Mohammad
    Assistant Professor Applied Mathematics, Payame Noor University, تهران, Iran
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