Zhi-xing SUN, Zhong-gai ZHAO, Fei LIU. Near-Infrared Spectral Modeling Based on Stacked Supervised Auto-Encoder[J]. Spectroscopy and Spectral Analysis, 2022, 42(3): 749
- Spectroscopy and Spectral Analysis
- Vol. 42, Issue 3, 749 (2022)
Fig. 1. The original spectra of corn
Fig. 2. The original spectra of yellow rice wine
Fig. 3. Structural of auto-encoder
Fig. 4. Structure of supervised auto-encoder structural
Fig. 5. Structure of stack supervised auto-encoder
(a): Stack supervised AE; (b): Supervised AE
(a): Stack supervised AE; (b): Supervised AE
Fig. 6. SSAE training process
Fig. 7. The influence of different learning rates and training times on the model (a), (b): Corn; (c), (d): Yellow wine
Fig. 8. Prediction results of different modeling methods for corn data
(a): PLSR model; (b): BP model; (c): SAE model; (d): SSAE model
(a): PLSR model; (b): BP model; (c): SAE model; (d): SSAE model
Fig. 9. Prediction results of different modeling methods for yellow wine data
(a): PLSR model; (b): BP model; (c): SAE model; (d): SSAE model
(a): PLSR model; (b): BP model; (c): SAE model; (d): SSAE model
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Table 1. Prediction results based on different pretreatment methods
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Table 2. Prediction results of corn data sets using different modeling methods
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Table 3. Prediction results of yellow wine data sets using different modeling methods
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