Identification of the Seaweed Fluorescence Spectroscopy Based on the PCA and KNN
Current years,the offing red tide of china is recurrent mutation,the direct and fast method which can analyze the amount and the kind of the phytoplankton is needed imperious.The sensitivity of three-dimensional fluorescence spectrum is high,three-dimensional fluorescence spectrum can show entire fingerprint information of fluorescent light that in the range of excitation and emission wavelength,but the dimension of three-dimensional fluorescence spectrum is higher,the characteristic spectrum of different kinds pelagic plant are multifarious,it is complex identification.The article use the method of PCA feature extraction,the spectroscopic data matrix of pelagic plant is analyzed from the perspective of independence,characteristic number sample which using PCA to extract is sorted by feature abstraction combine sorting method of KNN.The correct laboratory sorting of seaweed is realized.Experimental result indicate,this method can identify the chief component of admixture seaweed,the high dimensional spectroscopy information of seaweed is proceed effective feature extraction,the sorting speed is increase greatly,the discrimination of sorting is reach 89％ percent,the identifying effect is better.
PCA KNN three-dimensional fluorescence spectroscopy recognition Seaweed
Lv Jiangtao Gu Qiongchan Zhang Baojian Liang Liqin
Department of Automation Engineering,Northeastern University at Qinhuangdao Qinhuangdao,China College of information science and engineering,Northeastern University Shen Yang,China
国际会议
秦皇岛
英文
84-87
2010-11-05（万方平台首次上网日期，不代表论文的发表时间）