Classificação de solos utilizando redes neurais artificiais (RNA)
The work uses the Artificial Neural Networks (ANN) method to classify soils based on textural characteristics, such as percentages of sand, silt and clay. This implementation has advantages, including the ability to learn complex patterns from data and offer accurate computational solutions to probl...
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| Autores principales: | , |
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| Formato: | Artículo |
| Lenguaje: | portugués |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://dialnet.unirioja.es/servlet/oaiart?codigo=10265557 |
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| Sumario: | The work uses the Artificial Neural Networks (ANN) method to classify soils based on textural characteristics, such as percentages of sand, silt and clay. This implementation has advantages, including the ability to learn complex patterns from data and offer accurate computational solutions to problems related to soil classification. The main objective of the work is to evaluate the effectiveness of ANN in categorizing different types of soil based on well-defined limits, such as the maximum percentage of sand for silty soils. The results demonstrated that, with learning cycles and adjustments in connection weights, the ANN was able to correctly classify the tested samples, standing out as a promising tool for textural analysis in the context of agricultural engineering. |
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