图 书 馆
一种机器学习的发情检测方法Towards Sustainable Dairy Management - A Machine Learning Enhanced Method for Estrus Detection |
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| 课程网址: | http://videolectures.net/kdd2019_fauvel_masson_fromont/ |
| 主讲教师: | Kevin Fauvel |
| 开课单位: | 法国国家信息与自动化研究学院 |
| 开课时间: | 2020-03-02 |
| 课程语种: | 英语 |
| 中文简介: |  我们的研究通过机器学习方法应对了奶牛场中牛奶生产资源利用效率的挑战。繁殖是奶牛场表现的关键因素，因为牛奶的生产始于小牛的出生。因此，检测发情期（这是母牛容易怀孕的唯一时期）对于农场效率至关重要。我们的目标是增强发情检测（性能，可解释性），尤其是在目前尚未检测到的无声发情（占总发情的35％）上，并允许农民依靠基于可承受的数据（活动，温度）的自动发情检测解决方案。在本文中，我们首先提出一种具有现实世界数据分析的新颖方法，以通过机器学习方法解决行为和沉默发情检测。其次，我们提出LCE，这是一种基于本地级联的算法，在其检测无声发情的能力的驱动下，该算法明显优于典型的商业发情检测解决方案。然后，我们的研究揭示了动情传感器部署在发情检测中的关键作用。最后，我们提出了一种基于全局和局部（行为与静默）算法可解释性（SHAP）的方法，以减少发情检测解决方案中的不信任感。 |
| 课程简介: | Our research tackles the challenge of milk production resource use efficiency in dairy farms with machine learning methods. Reproduction is a key factor for dairy farm performance since cows milk production begin with the birth of a calf. Therefore, detecting estrus, the only period when the cow is susceptible to pregnancy, is crucial for farm efficiency. Our goal is to enhance estrus detection (performance, interpretability), especially on the currently undetected silent estrus (35% of total estrus), and allow farmers to rely on automatic estrus detection solutions based on affordable data (activity, temperature). In this paper, we first propose a novel approach with real-world data analysis to address both behavioral and silent estrus detection through machine learning methods. Second, we present LCE, a local cascade based algorithm that significantly outperforms a typical commercial solution for estrus detection, driven by its ability to detect silent estrus. Then, our study reveals the pivotal role of activity sensors deployment in estrus detection. Finally, we propose an approach relying on global and local (behavioral versus silent) algorithm interpretability (SHAP) to reduce the mistrust in estrus detection solutions. |
| 关 键 词: | 机器学习; 发情检查; 动情传感器 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-04-29：zhouxj |
| 最后编审: | 2020-05-25：chenxin |
| 阅读次数: | 69 |