LEOCADIO
HONTORIA GARCÍA
TITULAR DE UNIVERSIDAD
FLORENCIA MARINA
ALMONACID CRUZ
CATEDRATICO DE UNIVERSIDAD
Publications by the researcher in collaboration with FLORENCIA MARINA ALMONACID CRUZ (12)
2014
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A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator
Energy Conversion and Management, Vol. 85, pp. 389-398
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Virtual laboratory for the training and learning of the subject solar resource: OrientSol 2.0
Proceedings of XI Tecnologias Aplicadas a la Ensenanza de la Electronica (Technologies Applied to Electronics Teaching), TAEE 2014
2013
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Generation of ambient temperature hourly time series for some Spanish locations by artificial neural networks
Renewable Energy, Vol. 51, pp. 285-291
2012
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A simplified method for estimating direct normal solar irradiation from global horizontal irradiation useful for CPV applications
Renewable and Sustainable Energy Reviews, Vol. 16, Núm. 8, pp. 5529-5534
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Artificial neural networks for the generation of direct normal solar annual irradiance synthetic series
AIP Conference Proceedings
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Calculation of direct normal irradiation from global horizontal irradiation
AIP Conference Proceedings
2011
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Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks
Energy, Vol. 36, Núm. 1, pp. 375-384
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Two new applications of artificial neural networks: Estimation of instantaneous performance ratio and of the energy produced by PV generators
Studies in Fuzziness and Soft Computing, Vol. 269, pp. 199-232
2010
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Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods
Renewable Energy, Vol. 35, Núm. 5, pp. 973-980
2009
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Characterisation of Si-crystalline PV modules by artificial neural networks
Renewable Energy, Vol. 34, Núm. 4, pp. 941-949
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Estimation of the energy of a PV generator using artificial neural network
Renewable Energy, Vol. 34, Núm. 12, pp. 2743-2750
2006
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Artificial neural networks applied in PV systems and solar radiation
Artificial Intelligence in Energy and Renewable Energy Systems (Nova Science Publishers, Inc.), pp. 163-200