Spectroscopy and Spectral Analysis, Volume. 41, Issue 8, 2556(2021)
Chlorophyll Content Estimation of Northeast Japonica Rice Based on Improved Feature Band Selection and Hybrid Integrated Modeling
Fig. 5. Feature band selection results based on SPA algorithm
(a): Number of the best feature bands in the sample model; (b): Distribution of extracted feature bands
Fig. 7. Feature band selection results based on RF and fpb-RF algorithms
(a): RF algorithm; (b): fpb-RF algorithm
Fig. 8. GPR-P model prediction results of different feature band extraction methods
(a): CC-SPA algorithm; (b): RF algorithm; (c): fpb-RF algorithm
Fig. 9. PLSR model prediction results of different feature band extraction methods
(a): CC-SPA algorithm; (b): RF algorithm; (c): fpb-RF algorithm
Fig. 10. LSSVM model prediction results of different feature band extraction methods
(a): CC-SPA algorithm; (b): RF algorithm; (c): fpb-RF algorithm
Fig. 11. BP model prediction results of different feature band extraction methods
(a): CC-SPA algorithm; (b): RF algorithm; (c): fpb-RF algorithm
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Tan LIU, Tong-yu XU, Feng-hua YU, Qing-yun YUAN, Zhong-hui GUO, Bo XU. Chlorophyll Content Estimation of Northeast Japonica Rice Based on Improved Feature Band Selection and Hybrid Integrated Modeling[J]. Spectroscopy and Spectral Analysis, 2021, 41(8): 2556
Category: Research Articles
Received: Jun. 4, 2020
Accepted: --
Published Online: Sep. 8, 2021
The Author Email: LIU Tan (liutan_0822@126.com)