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- W2364672082 abstract "Using hyper-spectral technology to explore the quantitative estimation of soil organic matter content is of great significance for developing precision agriculture.Firstly,according to the measured data in Hengshan county,Shanxi province,the paper used one-order differential of logarithm to transform the collecting soil hyper-spectral data,and then respectively used linear regression analysis,fuzzy recognition method and artificial neural network to establish hyper-spectral soil organic matter estimation model,finally through the contrast analysis on the precision,the optimal spectrum inversion model was found out.The results showed that in the fuzzy recognition model,R2 is 0.973,and RMSE is 0.0468%,better than in both linear regression model and BP artificial neural network model.Therefore,soil organic matter hyper-spectral estimation should not only be absorbed in spectra mechanism research but also strengthen modeling methods innovation." @default.
- W2364672082 created "2016-06-24" @default.
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- W2364672082 date "2014-01-01" @default.
- W2364672082 modified "2023-09-23" @default.
- W2364672082 title "Contrast research on soil organic matter estimation model using hyper-spectral data" @default.
- W2364672082 hasPublicationYear "2014" @default.
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