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| Mehri,M; Ghazaghi,M. |
| A uniform design (UD) was used to construct models to explain the growth response of Japanese quails to dietary metabolizable energy (ME), and digestible methionine (dMet) and lysine (dLys) under tropical condition. In total, 100 floor pens with seven birds each were fed 25 UD different diets containing 25 ME (2808-3092 kcal/kg), dMet (0.31-0.49% of diet), and dLys (0.91-1.39% of diet) levels from 7 to 14 d of age. A platform of artificial neural network based on UD (ANN-UD) was generated to describe the growth response of the birds to dietary inputs using random search. Artificial neural networks of body weight gain (BWG) and feed conversion ratio (FCR) were optimized using random search algorithm. The optimization the ANN-UD results showed that maximum... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Quail chick; Nutritional requirement; Uniform design; Neural network. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2014000300013 |
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| Zhang,Guangya; Ge,Huihua. |
| Background: Support vector machine (SVM), a novel powerful machine learning technology, was used to develop the non-linear quantitative structure-property relationship (QSPR) model of the G/11 xylanase based on the amino acid composition. The uniform design (UD) method was applied to optimize the running parameters of SVM for the first time. Results: Results showed that the predicted optimum temperature of leave-one-out (LOO) cross-validation fitted the experimental optimum temperature very well, when the running parameter C, ξ, and γ was 50, 0.001 and 1.5, respectively. The average root-mean-square errors (RMSE) of the LOO cross-validation were 9.53ºC, while the RMSE of the back propagation neural network (BPNN), was 11.55ºC. The... |
| Tipo: Journal article |
Palavras-chave: Amino acid composition; Optimum temperature; Support vector machine; Uniform design; Xylanase. |
| Ano: 2012 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582012000100007 |
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