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通过自动称重系统增强韩国牛 (Hanwoo) 体重估计的多阶段数据处理

Dong-Hyeon Kim¹, Jae-Woo Song², Hyunjin Cho³

¹Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Republic of Korea.

Animals : an open access journal from MDPI

|June 26, 2025

概括

这项研究开发了一种算法,以提高牛的自动称量系统 (AWS) 准确性. 改进后的系统可靠地测量方向重量,支持智能畜牧业的精准养.

科学领域:

农业工程农业工程
动物科学动物科学
数据科学数据科学数据科学

背景情况:

自动称重系统 (AWS) 对于现代智能畜牧业至关重要.
由于环境因素和动物活动造成的高测量变化挑战了AWS的准确性.
准确的体重监测对于有效的牛管理至关重要.

研究的目的:

从AWS开发和验证一个算法,以提高方向盘重量测量的可靠性.
确保自动化体重测量与实际牛体重量保持一致.
改进畜牧管理中的数据驱动的精准养策略.

主要方法:

开发了一个三个阶段的算法:异常值检测/删除,重量估计和后处理调整.
图基的被用来检测异常值,以平均值为基础的估计.
后处理包括国家动物科学研究所的每日体重增加建议.

主要成果:

性能最好的算法实现了根的平均平方误差为12.35公斤.
开发的算法显示,单个方向盘的误差幅度低于10%.
该系统可靠地测量了牛的重量,证实了其适用于智能畜牧业的适用性.

结论:

开发的算法显著提高了AWS在方向盘重量测量的可靠性.
准确的,自动化的体重数据支持智能精准养和数据驱动的牲畜管理.
这项技术有助于推进智能畜牧养殖实践.

关键词:

汉宇汉宇汉宇汉宇牛的体重牛的体重处理数据的数据处理.畜牧业自动化畜牧业自动化统计统计统计统计统计

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