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使用基于肉类检查数据的状态空间模型评估农场的猪病发病率:时间序列分析
Tsubasa Narita1,2, Meiko Kubo3, Yuichi Nagakura4
1Graduate School of Medicine and Veterinary Medicine, University of Miyazaki, Miyazaki, 889-1692, Japan.
Porcine health management
|January 23, 2024
概括
本研究引入了一种状态空间模型,以使用屠宰检查数据客观评估猪病,改善肥管理和农场利能力. 该模型比传统的动物健康评估方法提供了更高的准确性和灵活性.
科学领域:
- 兽医流行病学 兽医流行病学
- 动物健康管理 动物健康管理
- 农业中的统计建模.
背景情况:
- 屠宰场检查数据为动物健康和肥管理提供了洞察力.
- 使用检查数据对农场疾病的客观评估仍然是一个挑战.
- 开发强大的方法对于改善猪健康和生产率至关重要.
研究的目的:
- 开发一种状态空间模型,使用屠宰检查数据来评估猪病率.
- 建立一个客观的方法来评估农场的肥管理.
- 提高疾病评估模型的准确性和灵活性.
主要方法:
- 使用了状态空间建模方法.
- 结合了 11 种猪病的 4 年屠宰场数据.
- 使用来自14个农场的数据验证了模型.
主要成果:
- 地方一级的状态空间模型在所有疾病中被证明是最有效的.
- 与ARIMA模型相比,状态空间模型显示出更高的准确性和灵活性.
- 没有确定季节性或趋势因素,这表明疾病在肥期间表现出来.
结论:
- 使用状态空间模型分析屠宰数据,可以客观评估肥管理.
- 通过数据分析更好地了解农场管理,可以提高利能力.
- 未来的研究应该探索非正常性和非线性,以获得更准确的模型.
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