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应用到自动奶系统中收集的数据的建模方法的文献综述
Laura Ozella1, Karina Brotto Rebuli1, Claudio Forte1
1Department of Veterinary Sciences, University of Turin, 10095 Grugliasco, TO, Italy.
Animals : an open access journal from MDPI
|June 28, 2023
概括
本综述强调了自动挤奶系统 (AMS) 的建模方法,发现机器学习在牛健康监测,特别是乳腺炎检测方面占主导地位. 在牛奶生产和行为分析方面需要进一步的研究.
科学领域:
- 乳制品科学 乳制品科学
- 农业工程 农业工程
- 动物科学动物科学
背景情况:
- 自动挤奶系统 (AMS) 是精密畜牧业不可或缺的一部分.
- 模拟方法在AMS中越来越多地用于乳制品管理.
- 需要对AMS中的建模应用进行全面的审查.
研究的目的:
- 审查和分析用于自动挤奶系统 (AMS) 的建模方法.
- 确定这些模型在牛健康,生产和行为方面的应用趋势.
- 突出研究差距和方法上的局限性.
主要方法:
- 60篇文章的系统审查,重点是AMS中的建模.
- 基于建模技术的研究分类 (机器学习,统计,模糊等). ) 的情况.
- 研究重点的分析:牛的健康,牛奶生产和行为/管理.
主要成果:
- 机器学习 (ML) 是主要的方法 (63%),主要用于检测奶牛健康 (82%),特别是乳腺炎.
- 牛奶生产 (11%) 和牛的行为/牧群管理 (7%) 是研究不足的领域.
- 在ML健康预测模型中发现了缺乏可靠的方法和阶级不平衡.
结论:
- ML显示了AMS在健康监测方面的巨大潜力,但需要方法的改进.
- 增加对牛奶产量预测和行为分析建模的关注对于全面的乳业管理至关重要.
- 解决ML模型中的类不平衡对于准确的健康预测至关重要.
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