Complex-valued forecasting of the global solar irradiation

dc.contributor.authorSaoud, L. Saad
dc.contributor.authorRahmoune, F.
dc.contributor.authorTourtchine, V.
dc.contributor.authorBaddari, K.
dc.date.accessioned2015-12-13T09:54:12Z
dc.date.available2015-12-13T09:54:12Z
dc.date.issued2013
dc.description.abstractIn this paper, a forecasting of the global solar irradiation in the complex-valued domain is proposed. A method to transform the meteorological data into complex values is developed and the Complex Valued Neural Network (CVNN) is used to model and forecast the daily and the hourly solar irradiation. The measured data of Tamanrasset city, Algeria (altitude: 1362 m; latitude: 22°48 N; longitude: 05°26 E) is used to validate the developed model. In the hourly solar irradiation case, the 24 h ahead will be forecasted using the combination of the past daily meteorological dataset. Several models are presented to test the feasibility and the performance of the CVNN for forecasting either daily or hourly solar irradiation for both multi input single output and multi input multi output strategies. Results obtained throughout this paper show that the CVNN technique is suitable for modeling and forecasting daily and hourly solar irradiationen_US
dc.identifier.issn19417012
dc.identifier.urihttps://dspace.univ-boumerdes.dz/handle/123456789/2526
dc.language.isoenen_US
dc.relation.ispartofseriesJournal of Renewable and Sustainable Energy/ Vol.5, N°4 (2013);
dc.subjectComplex-valued neural networksen_US
dc.subjectGlobal solar irradiationen_US
dc.subjectMeteorological dataen_US
dc.subjectModeling and forecasten_US
dc.subjectModeling and forecastingen_US
dc.subjectMulti input multi outputen_US
dc.subjectMulti input single outputsen_US
dc.subjectSolar irradiationen_US
dc.titleComplex-valued forecasting of the global solar irradiationen_US

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Complex-valued forecasting of the global solar irradiation.pdf
Size:
94.55 KB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: