On the Prediction of Chaotic Time Series using Neural Networks

On the Prediction of Chaotic Time Series using Neural Networks

Prediction techniques have the challenge of guaranteeing large horizons for chaotic time series. For instance, this paper shows that the majority of techniques can predict one step ahead with relatively low root-mean-square error (RMSE) and Symmetric Mean Absolute Percentage Error (SMAPE). However,...

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Bibliographic Details
Main Authors: Ericka Janet Rechy-ramirez, Astrid Maritza Gonzalez-zapata, Josue Alexis Martinez-garcia, Esteban Tlelo-cuautle
Format: Article
Language:English
Published: Akif AKGUL 2022-07-01
Series:Chaos Theory and Applications
Subjects:
chaotic time series
neural network
echo state network
long short-term memory
rmse
prediction technique
Online Access:https://dergipark.org.tr/en/download/article-file/2425475

Internet

https://dergipark.org.tr/en/download/article-file/2425475

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