Study on Five Typical Optimization Models of LSTM-Reference-Cited by-同舟云学术

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Study on Five Typical Optimization Models of LSTM

Published:2023-11-17 Issue: Volume:36 Page:298-303
ISSN:
Container-title:2023 China Automation Congress (CAC)
language:
Short-container-title:

Author:

Jianying Yu¹,Xuefei Zhou²,Shiqiang Lu³,Shaoze Xiao²,Ajun Wan⁴,Yalei Zhang²

Affiliation:

1. Tongji university School of Electronic and Information Engineering,Shanghai,China

2. Tongji university School of Environmental Science and Engineering,Shanghai,China

3. Shanghai Academy of Environmental Sciences Environmental Planning Institute,Shanghai,China

4. Tongji university School of Medicine,Shanghai,China

Funder

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10450150/10449968/10450860.pdf?arnumber=10450860

Reference60 articles.

1. Steel Grade Identification Based on Improved Convolution Neural Network [J];Weijian;Journal of Jilin University(information Science Edition),2018

2. A critical review of recurrent neural networks for sequence learning[J];Lipton;arXiv preprint,2015

3. Serial Order: A Parallel Distributed Processing Approach

4. Prediction of Alternaria and Pleospora concentrations from the meteorological forecast and artificial neural network in L’Aquila, Abruzzo (Central Italy)

5. Learning long-term dependencies with gradient descent is difficult

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