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Desenvolvimento e análise de uma rede neural artificial para estimativa da erosividade da chuva para o Estado de São Paulo
| Content Provider | Semantic Scholar |
|---|---|
| Author | Moreira, Michel Castro Cecílio, Roberto Avelino Pinto, Francisco Pruski, Fernando Falco |
| Copyright Year | 2006 |
| Abstract | Knowledge on rainfall erosivity (R) of particular sites is fundamental for soil loss estimation by the Universal Soil Loss Equation (USLE) and therefore highly important in conservation planning. In order to obtain the R value estimates for places where it is unknown, an artificial neural network (ANN) was developed for the state of Sao Paulo, and its accuracy compared with the Inverse Distance Weighted (IDW) interpolation method. The developed ANN presented a smaller mean relative error in the R estimation and a confidence index classified as "excellent", better than the IDW. ANN can therefore be used to estimate R values for soil use planning, management and conservation in Sao Paulo state. |
| Starting Page | 1069 |
| Ending Page | 1076 |
| Page Count | 8 |
| File Format | PDF HTM / HTML |
| DOI | 10.1590/S0100-06832006000600016 |
| Volume Number | 30 |
| Alternate Webpage(s) | http://www.scielo.br/pdf/rbcs/v30n6/a16v30n6.pdf |
| Alternate Webpage(s) | https://doi.org/10.1590/S0100-06832006000600016 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
