Modeling of soil penetration resistance using statistical analyses and artificial neural networks
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| Natura: | Artículo científico |
| Lingua: | en |
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Universidade Estadual de Maringá
2012
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| _version_ | 1876428061462757376 |
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| author | Fábio Lúcio Santos |
| author_facet | Fábio Lúcio Santos |
| contents | Modeling of soil penetration resistance using statistical analyses and artificial neural networks Fábio Lúcio Santos Valquíria Aparecida Mendes de Jesus Domingos Sárvio Magalhães Valente Agrociencias Modeling neural networks soil physical properties An important factor for the evaluation of an agricultural system’s sustainability is the monitoring of soil quality via its physical attributes. Th e physical attributes of soil, such as soil penetration resistance, can be used to monitor and evaluate the so il’s quality. Artificial Neural Networks (ANN) have been employed to solve many problems in agriculture, and the use of this techni que can be considered an alternative approach for predicting the penetration resistance produced by the soil’s basic properties, such as bulk density and water content. The aim of this wo rk is to perform an analysis of the soil penetration resistance behavior measured from the cone index under different levels of bulk density and water content using statistical analyses, specifically regression an alysis and ANN modeling. Both techniques show that soil penetration resistance is associated with soil bulk density and water content. The regression analysis presented a determination coefficient of 0.92 and an RMSE of 0.951, and the ANN modeling presented a determination coefficient of 0.98 and an RMSE of 0.084. The results show that the ANN modeling presented better results than the mathematical model obtained from regression analysis. 2012 artículo científico 1679-9275 https://www.redalyc.org/articulo.oa?id=303026599015 en http://www.redalyc.org/revista.oa?id=3030 Acta Scientiarum. Agronomy application/pdf Universidade Estadual de Maringá Acta Scientiarum. Agronomy (Brasil) Num.2 Vol.34 |
| format | Artículo científico |
| id | redalyc_303026599015 |
| institution | Redalyc |
| language | en |
| publishDate | 2012 |
| publisher | Universidade Estadual de Maringá |
| spellingShingle | Modeling of soil penetration resistance using statistical analyses and artificial neural networks Fábio Lúcio Santos Agrociencias Modeling neural networks soil physical properties Modeling of soil penetration resistance using statistical analyses and artificial neural networks Fábio Lúcio Santos Valquíria Aparecida Mendes de Jesus Domingos Sárvio Magalhães Valente Agrociencias Modeling neural networks soil physical properties An important factor for the evaluation of an agricultural system’s sustainability is the monitoring of soil quality via its physical attributes. Th e physical attributes of soil, such as soil penetration resistance, can be used to monitor and evaluate the so il’s quality. Artificial Neural Networks (ANN) have been employed to solve many problems in agriculture, and the use of this techni que can be considered an alternative approach for predicting the penetration resistance produced by the soil’s basic properties, such as bulk density and water content. The aim of this wo rk is to perform an analysis of the soil penetration resistance behavior measured from the cone index under different levels of bulk density and water content using statistical analyses, specifically regression an alysis and ANN modeling. Both techniques show that soil penetration resistance is associated with soil bulk density and water content. The regression analysis presented a determination coefficient of 0.92 and an RMSE of 0.951, and the ANN modeling presented a determination coefficient of 0.98 and an RMSE of 0.084. The results show that the ANN modeling presented better results than the mathematical model obtained from regression analysis. 2012 artículo científico 1679-9275 https://www.redalyc.org/articulo.oa?id=303026599015 en http://www.redalyc.org/revista.oa?id=3030 Acta Scientiarum. Agronomy application/pdf Universidade Estadual de Maringá Acta Scientiarum. Agronomy (Brasil) Num.2 Vol.34 |
| title | Modeling of soil penetration resistance using statistical analyses and artificial neural networks |
| topic | Agrociencias Modeling neural networks soil physical properties |
| url | https://www.redalyc.org/articulo.oa?id=303026599015 |