Dairy Cattle Movement Detecting Technology Using Support Vector Machine


HaoEn Zhou,LingYin,and CaiXing Liu College of Informatics,South China Agricultural University,510642 GuangZhou,China


In this paper,the dairy cattle movement detecting technology based on 3-axis acceleration sensor information fusion is presented. For they show ideal performance in generalization and optimization, Support vector machines are used to build an information fusion model for dairy cattle’s behavior classification. The data feature of the support vector machine fusion model is derived from 3-axis acceleration data. RBF function is used as the model’s kernel function. The genetic algorithm is used to optimize the parameters of the kernel function. The training and testing results show that using genetic algorithm for kernel function parameter searching has good ability to optimize the fusion model.


Dairy cattle movement detection; support vector machine; genetic algorithm


To explore the background and basis of the node document

Springer Journals Database

Total: 0 articles

Similar documents

Documents that have the similar content to the node document