The increase of dimension will increase the complexity of physical behavior sensing data,resul-ting in its distribution feature space being infinitely enlarged.Therefore,a feature extraction method for physical behavior sensing data based on finite dimensional space is proposed.The association rule mining a-nalysis method is used to calculate the data ambiguity and determine the limited space region of the physical behavior.In finite dimensional space,the eigenvalues of sensing data are calculated by adaptive optimiza-tion method.The feature attributes of physical behavior sensing data are detected,the output of data distri-bution fusion mapping is calculated,and the motion behavior feature extraction model is constructed.The experiment results show that the proposed method has a good spatial clustering effect on physical data,can fix the data in a finite dimensional space,and the accuracy of data feature extraction is always above 95％.
关键词
有限维空间/运动行为/传感数据/关联规则项挖掘/特征提取
Key words
finite dimensional space/physical behavior/sensing data/mining association rule items/fea-ture extraction
维普
万方数据