Grid-interpolation data pre-processor for radial basis function network solar cell model
| Autor: | Abdulrahman Al-Ibrahim, Gurvinder S. Virk, Mohammad AbdulHadi |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Data processing
Engineering Radial basis function network Artificial neural network Computer simulation Renewable Energy Sustainability and the Environment business.industry Electrical engineering Energy Engineering and Power Technology Grid Pre processor law.invention Fuel Technology Nuclear Energy and Engineering law Solar cell business Algorithm Interpolation |
| Zdroj: | International Journal of Energy Research. 27:615-624 |
| ISSN: | 1099-114X 0363-907X |
| Popis: | In this work, a radial basis function network model of solar cells is developed and validated against measured data. A grid-interpolation based data pre-processor is developed to prepare the training data from non-uniformly distributed measured data obtained via normal operation of the solar cells. Simulation results show that the pre-processor facilitates training, and that the resulting model is accurate under conditions sufficiently represented by the training data. The model matches measured data more accurately compared to conventional solar cell models. Copyright © 2003 John Wiley & Sons, Ltd. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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