外文摘要：This work presents a model based on artificial neural network (ANN) applied to predict water consumption in Brazilian dairy farms. Inputs were simple process data such as number of lactating cows, milk productivity, type of management, among others, with low computational cost and satisfactory data prediction. Data used for ANN training was acquired during two years from 31 farms in semi -confined dairy production. The analysis of the results was based on the following statistical models' indicators: R2 (Coefficient of determination), BIAS (trend coefficient), MAE (mean absolute error), RMSE (Root -meansquare deviation), NRMSE (percentage of the mean of the observations) and RAE (Relative absolute error). After performing the ANN training, the results showed good accuracy to predict water consumption in Brazilian dairy farms, with an average absolute error of 28.4% being obtained. On the other hand, considering the dataset used for ANN validation, an average absolute error of 48% was obtained.
外文关键词：Lactating Cows;Semi-confined;Water Efficiency;Water Meter
作者：Osaki, Marcia Regina;Palhares, Julio Cesar Pascale;Aguiar, Fernando Guimaraes
作者单位：Univ Virtual Estado Sao Paulo;Embrapa Pecuaria Sudeste;Univ Fed Sao Carlos
期刊名称：BIOSCIENCE JOURNAL
期刊影响因子：0.0
出版年份：2024
出版刊次：40
原文传递申请：江苏省科技资源（工程技术文献）统筹服务平台