用于家禽业管理的人工神经网络:基于肉鸡生产链的仿真

IF 0.4 Q4 Veterinary
Elisar Camilotti, T. Q. Furian, K. Borges, D. T. Rocha, V. P. Nascimento, H. L. Moraes, C. Salle
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引用次数: 0

摘要

摘要本研究的目的是利用人工神经网络(ANN)模型预测生产指标,并确定其对家禽整合系统的潜在经济影响。选取肉鸡种鸡场、一个孵化场、肉鸡生产群和一个屠宰场的40个动物技术和生产参数作为变量。针对“可售孵化”、“第5周末重量”、“部分谴责”和“全部谴责”4个输出变量建立人工神经网络模型,分析其与多重决定系数(R2)、相关系数(R)、平均误差(E)、均方误差(MSE)和均方根误差(RMSE)的关系。对生产情景进行了模拟,并对经济影响进行了估计。经验证,该人工神经网络模型适用于模拟生产场景。对于“可销售孵化”而言,孵卵器和卵储存期可能会增加经济收益。对于“第5周结束时的权重”,谱系(A)对于增加收益很重要。然而,肉鸡体重在第一周末可能没有显著影响。鸡群性别(雌性)可能会影响“部分谴责”率,而雏鸟第一天的体重可能不会。对于“总谴责”,鸡群性别和鸡的类型可能不会影响谴责率,但死亡率和肉鸡体重可能有显著影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial neural networks for the management of poultry industry: a simulation based on the broiler production chain
Abstract The aim of this study was to predict production indicators and to determine their potential economic impact on a poultry integration system using artificial neural networks (ANN) models. Forty zootechnical and production parameters from broiler breeder farms, one hatchery, broiler production flocks, and one slaughterhouse were selected as variables. The ANN models were established for four output variables: “saleable hatching”, “weight at the end of week 5,” “partial condemnation,” and “total condemnation” and were analyzed in relation to the coefficient of multiple determination (R2), correlation coefficient (R), mean error (E), mean squared error (MSE), and root mean square error (RMSE). The production scenarios were simulated and the economic impacts were estimated. The ANN models were suitable for simulating production scenarios after validation. For “saleable hatching”, incubator and egg storage period are likely to increase the financial gains. For “weight at the end of the week 5” the lineage (A) is important to increase revenues. However, broiler weight at the end of the first week may not have a significant influence. Flock sex (female) may influence the “partial condemnation” rates, while chick weight at first day may not. For “total condemnation”, flock sex and type of chick may not influence condemnation rates, but mortality rates and broiler weight may have a significant impact.
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来源期刊
Ciencia Animal Brasileira
Ciencia Animal Brasileira Veterinary-Veterinary (all)
CiteScore
0.50
自引率
0.00%
发文量
44
审稿时长
28 weeks
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