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  • 02월 22일 16시 이후 : 초록수정 불가능, 일정확인 및 검색만 가능

Method to improve discrimination using movingwindow principal component analysis(MWPCA) for origin of products

등록일
2008년 2월 14일 11시 23분 21초
접수번호
1306
발표코드
30P240포 이곳을 클릭하시면 발표코드에 대한 설명을 보실 수 있습니다.
발표시간
목 <발표Ⅰ>
발표형식
포스터
발표분야
분석화학
저자 및
공동저자
이상욱, 정회일
한양대학교 화학과,
A new discrimination method called the moving-window principal component analysis (MW-PCA) has been developed and its performance has been evaluated using several spectroscopic datasets. The main concept of MW-PCA was to combine moving-window system and principal component analysis, and then using an effective algorithm of error rate to obtain a value of percent of a separation. To evaluate its discrimination performances, four different spectroscopic datasets were employed: (1) conventional and wide area illumination Raman spectra of a origin of rice, (2) near-infrared(NIR) of a origin of cnidium officinale, (3) a origin of carrot, (4) a origin of sesame. Since the method of MW-PCA is different from other algorism and great to separate groups. Combining moving-window and principal component analysis with using newly algorism of error rate provided better result of qualitative analysis.

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