A dilated convolution network-based LSTM model for multi-step prediction of chaotic time series

A dilated convolution network-based LSTM model for multi-step prediction of chaotic time series

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Abstract Aiming to solve the problems of low accuracy of multi-step prediction and difficulty in determining the maximum number of prediction steps of chaotic time series, a multi-step time series prediction model based on the dilated convolution network and long short-term memory (LSTM), named the...

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Bibliographic Details
Main Authors:	Wang, Rongxi (Author), Peng, Caiyuan (Author), Gao, Jianmin (Author), Gao, Zhiyong (Author), Jiang, Hongquan (Author)
Format:	Article
Language:	English
Published:	Springer International Publishing, 2021-09-20T17:17:10Z.
Subjects:	Article
Online Access:	Get fulltext

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