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	Provedor de dados CIGR Journal (2) Autor Olorunfemi, Idowu Ezekiel (2) Fasinmirin, Johnson Toyin (1) Olufayo, Ayorinde Akinlabi (1) Taiwo, Adeyemi Akinjide (1) YUSUF, Habeeb Ajibola (1) Palavra-chave Cumulative infiltration (1) Hydraulic conductivity (1) Soil water movement (1) Sorptivity (1) Total porosity (1) Tipo do documento Info:eu-repo/semantics/article (2) Ano 2020 (1) 2016 (1) País China (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Spatial analysis of soil hydraulic properties of an alfisol in Akure, Southwestern Nigeria CIGR Journal Olorunfemi, Idowu Ezekiel; Taiwo, Adeyemi Akinjide; Olufayo, Ayorinde Akinlabi; Fasinmirin, Johnson Toyin. The knowledge of soil hydraulic properties and processes leads to better predictions of both agricultural and environment impact. The objectives of this research are to determine, predict and compare the relationship between measured and estimated soil hydraulic properties and also spatially characterize these properties using geostatistics. Mini disc infiltrometer at a suction rate of 2 cm per second was used for the determination of soil hydraulic properties at different points of an alfisol in Nigeria. Soil samples (100, 200 and 300 mm depths) were also analyzed to determine soil bulk density (BD), total porosity (PT) and water holding capacity (WHC). The coefficients of variation (CV) of the textural classes indicate a non-considerable variability of... Tipo: Info:eu-repo/semantics/article Palavras-chave: Sorptivity; Cumulative infiltration; Hydraulic conductivity; Soil water movement; Total porosity. Ano: 2016 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/3418 ESTIMATION OF EVAPOTRANSPIRATION RATE IN THE SAHELIAN REGION OF NIGERIA USING GENERALIZED REGRESSION NEURAL NETWORK AND FEED FORWARD NEURAL NETWORK CIGR Journal Olorunfemi, Idowu Ezekiel; YUSUF, Habeeb Ajibola. Artificial Neural Network (ANN) has been employed by researchers in obtaining accurate estimates of evapotranspiration rate. Generalized Regression Neural Network (GRNN) and Feed Forward Back Propagation Neural Network (FFBP NN) were used to estimate evapotranspiration rate in Kano State, Northern Nigeria to ascertain its modelling accuracy under less input parameters. A 25-year monthly - time step of climatological data was collected from IITA (International Institute of Tropical Agriculture) station. The data was grouped into 12 different input combination with training and validation sets. GRNN results indicate the lowest performance ranking as the lone solar radiation input combination (GRNNSr) having R = 0.3603, R2 = 0.1298, MSE = 1.4356, RMSE = 1.982... Tipo: Info:eu-repo/semantics/article Ano: 2020 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/5889 Registros recuperados: 2 Primeira ... 1 ... Última

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