Influence of LPLS algorithm parameters on NIR veracity
The theory of local partial least square (LPLS) algorithm was described based on locally weighted regression algorithm (LWR). The influence of data processing parameters, such as principal component numbers and local set-up sample number in LPLS mode, on the NIR veracity was studied with homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Results showed that for nicotine model, the principal component number decided by cross validation was not the best choice, and better results could be achieved by reducing the principal component number; using 30-50 samples to set up NIR model, the veracity of total sugar, total nitrogen, and nicotine could be improved by 7%, 14% and 10%, respectively. So, LPLS algorithm can effectively improve NIR model's veracity, and is a good method to set up robust NIR models.
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2007 |
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| Erschienen: |
2007 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:27 |
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| Enthalten in: |
Guang pu xue yu guang pu fen xi = Guang pu - 27(2007), 2 vom: 01. Feb., Seite 262-4 |
| Sprache: |
Chinesisch |
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| Beteiligte Personen: |
Li, Jun-hui [VerfasserIn] |
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| Themen: |
6M3C89ZY6R |
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| Anmerkungen: |
Date Completed 07.06.2010 Date Revised 13.12.2023 published: Print Citation Status MEDLINE |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM170405907 |
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| 245 | 1 | 0 | |a Influence of LPLS algorithm parameters on NIR veracity |
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| 500 | |a Date Revised 13.12.2023 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a The theory of local partial least square (LPLS) algorithm was described based on locally weighted regression algorithm (LWR). The influence of data processing parameters, such as principal component numbers and local set-up sample number in LPLS mode, on the NIR veracity was studied with homemade grating diffuse NIR instrument using Yunnan flue-cured tobacco. Results showed that for nicotine model, the principal component number decided by cross validation was not the best choice, and better results could be achieved by reducing the principal component number; using 30-50 samples to set up NIR model, the veracity of total sugar, total nitrogen, and nicotine could be improved by 7%, 14% and 10%, respectively. So, LPLS algorithm can effectively improve NIR model's veracity, and is a good method to set up robust NIR models | ||
| 650 | 4 | |a English Abstract | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 7 | |a Carbohydrates |2 NLM | |
| 650 | 7 | |a Nicotine |2 NLM | |
| 650 | 7 | |a 6M3C89ZY6R |2 NLM | |
| 650 | 7 | |a Nitrogen |2 NLM | |
| 650 | 7 | |a N762921K75 |2 NLM | |
| 700 | 1 | |a Qin, Xi-yun |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Wen-juan |e verfasserin |4 aut | |
| 700 | 1 | |a Cai, Gui-min |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Yu-hong |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Long-lian |e verfasserin |4 aut | |
| 700 | 1 | |a Chang, Zhi-qiang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Li-li |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Lu-da |e verfasserin |4 aut | |
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