Most influential variables for solar radiation forecasting using artificial neural networks

B. M. Alluhaidah; S. H. Shehadeh; M. E. El-Hawary

doi:10.1109/EPEC.2014.36

Most influential variables for solar radiation forecasting using artificial neural networks

B. M. Alluhaidah, S. H. Shehadeh, M. E. El-Hawary

Arts and Humanities

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

25 Citations (Scopus)

Original language	English
Title of host publication	Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	71-75
Number of pages	5
ISBN (Electronic)	9781479960385
DOIs	https://doi.org/10.1109/EPEC.2014.36
Publication status	Published - Feb 27 2014
Event	2014 Electrical Power and Energy Conference, EPEC 2014 - Calgary, Canada Duration: Nov 12 2014 → Nov 14 2014

Publication series

Name	Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014

Conference

Conference	2014 Electrical Power and Energy Conference, EPEC 2014
Country/Territory	Canada
City	Calgary
Period	11/12/14 → 11/14/14

ASJC Scopus Subject Areas

Electrical and Electronic Engineering
Energy Engineering and Power Technology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/EPEC.2014.36

Cite this

Alluhaidah, B. M., Shehadeh, S. H., & El-Hawary, M. E. (2014). Most influential variables for solar radiation forecasting using artificial neural networks. In Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014 (pp. 71-75). Article 7051678 (Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EPEC.2014.36

Most influential variables for solar radiation forecasting using artificial neural networks. / Alluhaidah, B. M.; Shehadeh, S. H.; El-Hawary, M. E.
Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 71-75 7051678 (Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014).

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

Alluhaidah, BM, Shehadeh, SH & El-Hawary, ME 2014, Most influential variables for solar radiation forecasting using artificial neural networks. in Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014., 7051678, Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 71-75, 2014 Electrical Power and Energy Conference, EPEC 2014, Calgary, Canada, 11/12/14. https://doi.org/10.1109/EPEC.2014.36

Alluhaidah BM, Shehadeh SH, El-Hawary ME. Most influential variables for solar radiation forecasting using artificial neural networks. In Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 71-75. 7051678. (Proceedings - 2014 Electrical Power and Energy Conference, EPEC 2014). doi: 10.1109/EPEC.2014.36

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Most influential variables for solar radiation forecasting using artificial neural networks

Publication series

Conference

ASJC Scopus Subject Areas

UN SDGs

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