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Deep Learning in Power Systems Research:A Review

Mahdi Khodayar Guangyi Liu Jianhui Wang Mohammad E.Khodayar

中国电机工程学会电力与能源系统学报（英文版）2021，Vol.7Issue(2)：209-220,12.

中国电机工程学会电力与能源系统学报（英文版）2021，Vol.7Issue(2)：209-220,12.DOI:10.17775/CSEEJPES.2020.02700

Deep Learning in Power Systems Research:A Review

Mahdi Khodayar ¹Guangyi Liu ²Jianhui Wang ³Mohammad E.Khodayar⁴

作者信息

1. Global Energy Interconnection Research Institute North America(GEIRI North America),San Jose,CA,USA
2. Department of Computer Science at the University of Tulsa,Tulsa,OK,USA
3. Envision Digital,Redwood City,CA,USA
4. Department of Electrical and Computer Engineering of Southern Methodist University,Dallas,TX,USA
折叠

摘要

关键词

Autoencoder/convolution neural network/deep learning/discriminative model/deep belief network/generative architecture/variational inference

Key words

Autoencoder/convolution neural network/deep learning/discriminative model/deep belief network/generative architecture/variational inference

引用本文复制引用

Mahdi Khodayar,Guangyi Liu,Jianhui Wang,Mohammad E.Khodayar..Deep Learning in Power Systems Research:A Review[J].中国电机工程学会电力与能源系统学报（英文版）,2021,7(2):209-220,12.

基金项目

This work was supported by the Science and Technology Project of State Grid Corporation of China(No.5455HJ180018) （No.5455HJ180018）

中国电机工程学会电力与能源系统学报（英文版）

OACSCDCSTPCDEISCI

ISSN：2096-0042

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