Abstract：A new spectrum quantitative analysis method based on Bootstrap-SVM model with small sample set is proposed in this paper. To build the spectrum quantitative analysis model for bitumen penetration index, altogether 29 bitumen samples were collected from 6 companies. Based on the collected 29 bitumen samples, spectrum quantitative analysis model with proposed method for predicting bitumen penetration index has been built. To verify the feasibility and effectiveness of the proposed method, the comparative experiments of predicting the bitumen sample penetration index with the proposed method, partial least squares (PLS) and support vector machine (SVM) have also been done. Comparative experiment results have verified that the minimum prediction root mean squared error (RMSE) is achieved by using the proposed Bootstrap-SVM model with the small sample set. The proposed method provides a new way to solve the problem of building the spectrum quantitative analysis model with small sample set.
Key words：Spectrum quantitative analysis;Small sample set;Bootstrap;Support vector machines;Partial least squares
马 啸，赵 众*，熊善海. 基于Bootstrap-SVM在小样本条件下光谱定量分析研究[J]. 光谱学与光谱分析, 2016, 36(05): 1571-1575.
MA Xiao, ZHAO Zhong*, XIONG Shan-hai. Spectrum Quantitative Analysis Based on Bootstrap-SVM Model with Small Sample Set. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36(05): 1571-1575.
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