Research Article
Dairy Cattle Movement Detecting Technology Using Support Vector Machine
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@INPROCEEDINGS{10.1007/978-3-642-29157-9_3, author={HaoEn Zhou and Ling Yin and CaiXing Liu}, title={Dairy Cattle Movement Detecting Technology Using Support Vector Machine}, proceedings={Wireless Communications and Applications. First International Conference, ICWCA 2011, Sanya, China, August 1-3, 2011, Revised Selected Papers}, proceedings_a={ICWCA}, year={2012}, month={5}, keywords={Dairy cattle movement detection support vector machine genetic algorithm}, doi={10.1007/978-3-642-29157-9_3} }- HaoEn Zhou
Ling Yin
CaiXing Liu
Year: 2012
Dairy Cattle Movement Detecting Technology Using Support Vector Machine
ICWCA
Springer
DOI: 10.1007/978-3-642-29157-9_3
Abstract
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.
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