Predicting a chaotic time series using a fuzzy neural network
From MaRDI portal
Publication:1818809
DOI10.1016/S0020-0255(98)10026-9zbMath0953.68590MaRDI QIDQ1818809
L. J. McDaid, L. P. Maguire, B. Roche, Thomas Martin McGinnity
Publication date: 27 June 2000
Published in: Information Sciences (Search for Journal in Brave)
Related Items (22)
Robustness of LSTM neural networks for multi-step forecasting of chaotic time series ⋮ Identification of fuzzy models using a successive tuning method with a variant identification ratio ⋮ Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons ⋮ A pseudorandom number generator based on piecewise logistic map ⋮ HYBRID FUZZY POLYNOMIAL NEURAL NETWORKS ⋮ A new approach to identification of input-driven dynamical systems from probability densities ⋮ Identification of stochastically perturbed autonomous systems from temporal sequences of probability density functions ⋮ Genetically optimized hybrid fuzzy set based polynomial neural networks ⋮ Keyed hash function based on a chaotic map ⋮ A matrix-based approach to solving the inverse Frobenius-Perron problem using sequences of density functions of stochastically perturbed dynamical systems ⋮ Stochastic stability of uncertain fuzzy recurrent neural networks with Markovian jumping parameters ⋮ A new approach to self-organizing fuzzy polynomial neural networks guided by genetic optimization ⋮ Smooth transition autoregressive models and fuzzy rule-based systems: Functional equivalence and consequences ⋮ Multi-layer self-organizing polynomial neural networks and their development with the use of genetic algorithms ⋮ Particle swarm optimization of ensemble neural networks with fuzzy aggregation for time series prediction of the Mexican Stock Exchange ⋮ One-way hash function construction based on 2D coupled map lattices ⋮ Identification of fuzzy relation models using hierarchical fair competition-based parallel genetic algorithms and information granulation ⋮ Prediction of multivariate chaotic time series with local polynomial fitting ⋮ The Dynamic Feedback Matrix Control for Multidimensional Chaotic Systems ⋮ The design of self-organizing neural networks based on PNS and FPNs with the aid of genetic optimization and extended GMDH method ⋮ Meta fuzzy functions based feed-forward neural networks with a single hidden layer for forecasting ⋮ Fuzzy radial basis function neural networks with information granulation and its parallel genetic optimization
Uses Software
Cites Work
This page was built for publication: Predicting a chaotic time series using a fuzzy neural network