A Multi-step Time Series Prediction Strategy in Deep Learning: Combination of Recursive Strategy and Multi-output by Dense Layer Strategy-Reference-Cited by-同舟云学术

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A Multi-step Time Series Prediction Strategy in Deep Learning: Combination of Recursive Strategy and Multi-output by Dense Layer Strategy

Published:2022-04 Issue: Volume: Page:
ISSN:
Container-title:2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)
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Author:

Liu Yuxuan¹

Affiliation:

1. University of Electronic Science and Technology of China,School of Information and Software Engineering,Chengdu,Sichuan,China,610051

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9948218/9948219/09948363.pdf?arnumber=9948363

Reference16 articles.

1. Hierarchical delay-memory echo state network: A model designed for multi-step chaotic time series prediction

2. Long-term prediction of blood pressure time series using ANFIS system based on DKFCM clustering

3. House Hold Energy Data——Time Series, 2020;gopinadhan,0

4. Batch normalization: accelerating deep network training by reducing internal covariate shift;ioffe;JMLR org,2015

5. Empirical evaluation of gated recurrent neural networks on sequence modeling;chung;ArXiv eprint,2014

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Novel Interval Forecast for K-Nearest Neighbor Time Series: A Case Study of Durian Export in Thailand;IEEE Access;2024

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