Research and Application of Optimal LSTM Combinatorial Model Based on Convolutional Neural Network-Reference-Cited by-同舟云学术

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Research and Application of Optimal LSTM Combinatorial Model Based on Convolutional Neural Network

Published:2023-08-26 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Computers, Information Processing and Advanced Education (CIPAE)
language:
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Author:

Cao Yihui¹,Li Yanan²,Zong Yingjie³

Affiliation:

1. Beijing Jiaotong University,School of Computer and Information Technology,Beijing,China

2. Xuzhou Medical University,School of Medical Imaging,Xuzhou,China

3. Sichuan University,College of Software Engineering,Chengdu,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10350193/10350194/10350293.pdf?arnumber=10350293

Reference13 articles.

1. A review on the application of deep learning in wind power forecasting;Wang;Applied Energy,2018

2. A review of wind power and wind speed forecasting methods with different time horizons;Mohammadi;Renewable and Sustainable Energy Reviews,2015

3. Wind speed forecasting using deep learning: A comparison study;Zhang;Renewable and Sustainable Energy Reviews,2017

4. CNN-LSTM for wind speed prediction;Li;Neural Computing and Applications,2017

5. Load forecasting model of integrated energy system based on CNN-LSTM[J];Zhang;Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition),2023

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