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- W2391520398 abstract "The hyper-spectra data of coniferous species,including Cunninghamia lanceolata,Pinus massoniana,Pinus thunbergii and Cedrus deodara,were collected using the FieldSpec HandheldTM of ASD Inc.in Winter 2005,2006 and 2008 respectively,and the efficient data of 160 samples were obtained through screening.All samples were divided randomly into two groups,one group with the 120 samples used as the calibrated set,and the other with the 40 samples as the calibrated set.The samples data were pretreated by the methods of smoothing and first derivative.The pretreated data were analyzed by Principal Component Analysis(PCA) and Genetic Algorithms(GA) methods,and then which were classified by Back Propagation(BP) and Support Vector Machine(SVM).The results show: the accuracy was 95% by PCA-BP neural network model,97.5% by PCA-SVM model,92.5% by GA-BP model,and 100% by GA-SVM model.The results show that the classification using the two methods combined with SVM does much better than that combined with BP,the selection of hyper-spectral band base on GA method is more efficient way,and which has a good foreground in the application." @default.
- W2391520398 created "2016-06-24" @default.
- W2391520398 creator A5019106443 @default.
- W2391520398 date "2010-01-01" @default.
- W2391520398 modified "2023-09-25" @default.
- W2391520398 title "Study on hyper-spectral dimension reduction and classification for main southern coniferous species" @default.
- W2391520398 hasPublicationYear "2010" @default.
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