Long Term Solar Radiation Forecast Using Computational Intelligence Methods
Joint Authors
Coelho, João Paulo
Boaventura-Cunha, José
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-12-10
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
The point prediction quality is closely related to the model that explains the dynamic of the observed process.
Sometimes the model can be obtained by simple algebraic equations but, in the majority of the physical systems, the relevant reality is too hard to model with simple ordinary differential or difference equations.
This is the case of systems with nonlinear or nonstationary behaviour which require more complex models.
The discrete time-series problem, obtained by sampling the solar radiation, can be framed in this type of situation.
By observing the collected data it is possible to distinguish multiple regimes.
Additionally, due to atmospheric disturbances such as clouds, the temporal structure between samples is complex and is best described by nonlinear models.
This paper reports the solar radiation prediction by using hybrid model that combines support vector regression paradigm and Markov chains.
The hybrid model performance is compared with the one obtained by using other methods like autoregressive (AR) filters, Markov AR models, and artificial neural networks.
The results obtained suggests an increasing prediction performance of the hybrid model regarding both the prediction error and dynamic behaviour.
American Psychological Association (APA)
Coelho, João Paulo& Boaventura-Cunha, José. 2014. Long Term Solar Radiation Forecast Using Computational Intelligence Methods. Applied Computational Intelligence and Soft Computing،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1015256
Modern Language Association (MLA)
Coelho, João Paulo& Boaventura-Cunha, José. Long Term Solar Radiation Forecast Using Computational Intelligence Methods. Applied Computational Intelligence and Soft Computing No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-1015256
American Medical Association (AMA)
Coelho, João Paulo& Boaventura-Cunha, José. Long Term Solar Radiation Forecast Using Computational Intelligence Methods. Applied Computational Intelligence and Soft Computing. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1015256
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1015256