结构相似子序列快速聚类算法及其在奶牛发情检测中的应用

准确高效的奶牛发情检测技术能够提高其受胎率、缩短胎间距,是改善奶牛繁殖效率和提高经济效益的重要手段。规模化、集约化养殖环境下,众多学术与科学研究证实奶牛行为方式和活动量是判断其是否发情的重要指标。目前常用奶牛行为决策方法主要是针对单点数据进行行为分类,而奶牛运动传感数据是按照时间顺序采集的多元时间序列数据,因此该文提出基于结构相似度的子序列段快速聚类算法（SC-SS,subsequence clustering based on structural similarity）,首先利用加速度一阶差分值将奶牛运动动态时间序列传感数据划分成若干子序列段,然后计算子序列段加速度值、能量、标准方差等特征...

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Bibliographic Details
Published in农业工程学报 Vol. 28; no. 15; pp. 107 - 112
Main Author 尹令 洪添胜 刘汉兴 刘财兴 王永波
Format Journal Article
LanguageChinese
Published 华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州510642%华南农业大学信息学院,广州510642%华南农业大学工程学院,广州510642 2012
Subjects
奶牛
时间序列分析
检测
结构相似度
行为研究
行为研究
结构相似度
时间序列分析
检测
奶牛
Online AccessGet full text
ISSN1002-6819
DOI10.3969/j.issn.1002-6819.2012.15.017

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Summary:准确高效的奶牛发情检测技术能够提高其受胎率、缩短胎间距,是改善奶牛繁殖效率和提高经济效益的重要手段。规模化、集约化养殖环境下,众多学术与科学研究证实奶牛行为方式和活动量是判断其是否发情的重要指标。目前常用奶牛行为决策方法主要是针对单点数据进行行为分类,而奶牛运动传感数据是按照时间顺序采集的多元时间序列数据,因此该文提出基于结构相似度的子序列段快速聚类算法（SC-SS,subsequence clustering based on structural similarity）,首先利用加速度一阶差分值将奶牛运动动态时间序列传感数据划分成若干子序列段,然后计算子序列段加速度值、能量、标准方差等特征结构相似度;最后根据各个子序列的结构相似度进行快速聚类。试验数据分析对比表明,SC-SS较常用K-means算法具有更高的运行效率,可更有效地完成奶牛行为分类,提高奶牛发情检测的准确率。
Bibliography:11-2047/S
Yin Ling ,Hong Tiansheng, Liu Hanxing, Liu Caixing, Wang Yongbo （1. Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, China; 2. College of lnformatics, South China Agricultural University, Guangzhou 510642, China; 3. College of Engineering, South China Agricultural University, Guangzhou 510642, China）
time series analysis, behavioral research, detectors, structural similarity （SSIM）, cow
The efficient and accurate estrus detection technology can enhance conception rates and shorten birth spacing of the breeding dairy cow, which is an important means for improving economic benefit. For the large-scale, intensive farming environment, the cow＇s behavior and activity is an important indicator to determine whether estrus which is confirmed by numerous academic and scientific research. Usually the cow＇s behavior decision-making methods are using the single point of data to classify behavior. However the cow＇s
ISSN:1002-6819
DOI:10.3969/j.issn.1002-6819.2012.15.017