Name
Title | ||
|---|---|---|
Neural representation of a solar collector with statistical optimization of the training set |
Abstract | ||
|---|---|---|
Alternative ways of energy producing are essential in a reality where natural resources have been scarce and solar collectors are one of these ways. However the mathematical modeling of solar collectors involves parameters that may lead to nonlinear equations. Due to their facility of solving nonlinear problems, ANN (i.e. Artificial Neural Networks) are presented here, as an alternative to represent these solar collectors with several advantages on other techniques of modeling, like linear regression. Techniques for selecting representative training sets are also discussed and presented in this paper. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/b97304 | IEA/AIE |
Keywords | Field | DocType |
natural resource,nonlinear equation,linear regression,mathematical model,artificial neural network | Training set,Data mining,Mathematical optimization,Nonlinear system,Regression analysis,Computer science,Artificial intelligence,Solar irradiance,Artificial neural network,Statistical analysis | Conference |
Volume | ISSN | ISBN |
3029 | 0302-9743 | 3-540-22007-0 |
Citations | PageRank | References |
2 | 0.61 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luis E. Zárate | 1 | 107 | 25.52 |
| Elizabeth Marques Duarte Pereira | 2 | 10 | 2.40 |
| João Paulo D. Silva | 3 | 4 | 1.30 |
| Renato Vimieiro | 4 | 27 | 4.33 |
| Antônia Sônia Cardoso Diniz | 5 | 4 | 1.30 |