Performance evaluation of deep recurrent neural networks architectures: Application to PV power forecasting

Mohamed Massaoudi, Ines Chihi, Lilia Sidhom, Mohamed Trabelsi, Shady S Refaat, Fakhreddine S Oueslati

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	2019 2nd International Conference on Smart Grid and Renewable Energy (SGRE)
Pages	1-6
Number of pages	6
Publication status	Published - 2019

Cite this

@inproceedings{25b1aae736c04953ae753b701206c546,

title = "Performance evaluation of deep recurrent neural networks architectures: Application to PV power forecasting",

author = "Mohamed Massaoudi and Ines Chihi and Lilia Sidhom and Mohamed Trabelsi and Refaat, {Shady S} and Oueslati, {Fakhreddine S}",

year = "2019",

language = "English",

pages = "1--6",

booktitle = "2019 2nd International Conference on Smart Grid and Renewable Energy (SGRE)",

}

TY - GEN

T1 - Performance evaluation of deep recurrent neural networks architectures: Application to PV power forecasting

AU - Massaoudi, Mohamed

AU - Chihi, Ines

AU - Sidhom, Lilia

AU - Trabelsi, Mohamed

AU - Refaat, Shady S

AU - Oueslati, Fakhreddine S

PY - 2019

Y1 - 2019

M3 - Conference contribution

SP - 1

EP - 6

BT - 2019 2nd International Conference on Smart Grid and Renewable Energy (SGRE)

ER -