Short-term wind speed prediction using Bayesian optimized LSTM network-Reference-Cited by-同舟云学术

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Short-term wind speed prediction using Bayesian optimized LSTM network

Published:2022-12-16 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Power and Renewable Energy Conference (IPRECON)
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Author:

Sharma Rohit Kumar¹,Namboodiri V Vishnu¹,Rathore Santosh Singh²,Goyal Rahul¹

Affiliation:

1. Indian Institute of Technology, Delhi,Department of Energy Science and Engineering,Delhi,India

2. ABV-Indian Institute of Information Technology and Management, Gwalior,Department of Information Technology,Gwalior,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10059458/10059467/10059475.pdf?arnumber=10059475

Reference16 articles.

1. A hybrid method for short-term wind speed forecasting based on Bayesian optimization and error correction

2. A long-term prediction approach based on long short-term memory neural networks with automatic parameter optimization by Tree-structured Parzen Estimator and applied to time-series data of NPP steam generators;nguyen;Applied Soft Computing Journal,2021

3. A Short-Term Wind Power Forecast Method via XGBoost Hyper-Parameters Optimization

4. Support vector machines for wind speed prediction

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. Advanced Forecasting of Wind Energy Generation Through Integration of AE-CLSTM;2024 International Conference on Green Energy, Computing and Sustainable Technology (GECOST);2024-01-17

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