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概率估计的最佳采样策略:农业检疫检查监测计划的应用
Huidi Ma1, Benjamin D Leibowicz1, John J Hasenbein1
1Operations Research and Industrial Engineering, The University of Texas at Austin, Austin, Texas, USA.
Risk analysis : an official publication of the Society for Risk Analysis
|November 11, 2024
概括
优化农业害虫检测,这项研究表明,采样更多的运输集装箱和更少的物品在每个是比目前的方法更有效. 这一战略提高了对农业安全的害虫风险评估准确性.
科学领域:
- 农业科学 农业科学
- 运营研究 运营研究
- 风险管理 风险管理
背景情况:
- 进口农业害虫对农业,粮食安全和生态系统构成重大威胁.
- 准确的风险评估对于有效的农业检疫和检查政策至关重要.
- 当前的检查协议通常依赖于容器级启发式,可能会限制准确性.
研究的目的:
- 开发一个优化的采样策略,用于在入境港口检测害虫.
- 引入路径级分析,以改善风险估计,与农业检疫检查监测 (AQIM) 计划的目标保持一致.
- 在资源限制下,解决采样容器与每个容器的盒子之间的权衡问题.
主要方法:
- 制定一个优化模型,以最大限度地减少害虫概率估计的平均平方误差.
- 用近似计算推导出最佳采样策略的分析解决方案.
- 该模型应用于长港对海运货物采样的案例研究.
主要成果:
- 相比于当前的AQIM协议,最佳策略始终倾向于采样更多的集装箱和每个集装箱更少的盒子.
- 当同一个容器内的害虫状态高度相关时,拟议策略的准确性得到了加强.
- 该研究量化了新方法在各种参数设置中的好处.
结论:
- 一种途径级采样方法提供了优越的害虫风险评估准确性.
- 建议从以集装箱为中心的采样转向更细粒度的采样策略.
- 建议收集盒级检查数据,以完善害虫相关性估计,并改善未来的AQIM操作.
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