Daily Solar Radiation Prediction Using LSTM Neural Networks-Reference-Cited by-同舟云学术

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Daily Solar Radiation Prediction Using LSTM Neural Networks

Published:2022-10-26 Issue: Volume: Page:
ISSN:
Container-title:2022 Global Energy Conference (GEC)
language:
Short-container-title:

Author:

Gider Veysel¹,Budak Cafer²,Izci Davut³,Ekinci Serdar⁴

Affiliation:

1. Rectorate Batman University,Distance Education Application and Research Center,Batman,Turkey

2. Dicle University,Department of Electric-Electronic Engineering,Diyarbakir,Turkey

3. Batman University,Department of Electronics and Automation,Batman,Turkey

4. Batman University,Department of Computer Engineering,Batman,Turkey

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9986512/9986518/09987055.pdf?arnumber=9987055

Reference18 articles.

1. A simplified LSTM neural networks for one day-ahead solar power forecasting;liu;IEEE Access,2021

2. Voice Conversion Based Augmentation and a Hybrid CNN-LSTM Model for Improving Speaker-Independent Keyword Recognition on Limited Datasets

3. Wavelet Decomposition and Convolutional LSTM Networks Based Improved Deep Learning Model for Solar Irradiance Forecasting

4. Diyarbakir IliIçn Günes Enerjisi Verilerinin Meteorolojik Standartlarda Olculmesive Analizi;kiliç;EMO Bilimsel Dergi,2016

5. Performance comparison of solar radiation forecasting between WRF and LSTM in Gifu, Japan

Cited by 2 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. Predictive Modeling of Solar Energy Production: A Comparative Analysis of Machine Learning and Time Series Approaches;2024 IEEE International Conference for Women in Innovation, Technology & Entrepreneurship (ICWITE);2024-02-16

2. LSTM based forecasting of the next day’s values of ionospheric total electron content (TEC) as an earthquake precursor signal;Earth Science Informatics;2023-06-26

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