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Evaluation of Deep Learning Models For Multi-Step Ahead Time Series Prediction PDF

22 Pages·2021·English
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by ['Dinibel Pérez']| 2021| 22 pages| English

About Evaluation of Deep Learning Models For Multi-Step Ahead Time Series Prediction

This document evaluates deep learning models for multi-step time series prediction. It compares simple recurrent neural networks, long short-term memory (LSTM) networks, bidirectional LSTM, encoder-decoder LSTM networks, and convolutional neural networks on benchmark time series datasets. The results show that bidirectional and encoder-decoder LSTM networks provide the best performance and accuracy for time series problems with different properties.

Detailed Information

Author:['Dinibel Pérez']
Publication Year:2021
Pages:22
Language:English
Format:PDF
Price:FREE
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