王清亚, 李福生, 江晓宇, 邬书良, 谢涛锋, 黄温钢. Quantitative Analysis of Soil Cadmium Content Based on Fusion of XRF Data and Vis-NIR Data[J]. 2020, 39(11): 1327-1333.DOI: doi:10.3969/j.issn.1004-4957.2020.11.003.
According to the characteristics of X-ray fluorescence spectrum and visible near infrared spectrum for soil in Nanji area of Poyang Lake
three quantitative analysis models for data fusion
including equal right fusion
co-addition fusion and outer product fusion based on least squares vector machine(LS-SVM) were established.Results showed that the models for equal right fusion and outer product fusion have better accuracy and stability than the single spectral quantitative analysis model has
in which the model for outer product fusion exhibits the best performance with a determination coefficient(R2) of 0.85
a root mean squared error(RMSEC) of 0.09
a root mean square error of prediction(RMSEP) of 0.06 and a relative percent deviation(RPD) of 2.41
satisfying the detection requirements.With the advantages of accuracy and reliability
the developed method could provide a reference for the study of soil heavy metal classification and grading method in China.