Camellia oleifera leaf carbon nitrogen ratio estimation method based on canopy hyperspectrum
The invention relates to the technical field of oil-tea camellia leaf carbon-nitrogen ratio estimation, in particular to an oil-tea camellia leaf carbon-nitrogen ratio estimation method based on canopy hyperspectrum. According to the method, a multi-layer feedforward neural network based on error re...
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| creator | YAN LIPENG DOU MIN TANG XUEHAI HUANG QINGFENG GAO XIANG WANG AQING KUANG FAN QIAN WENQI FU GENSHEN XU CHENG |
| description | The invention relates to the technical field of oil-tea camellia leaf carbon-nitrogen ratio estimation, in particular to an oil-tea camellia leaf carbon-nitrogen ratio estimation method based on canopy hyperspectrum. According to the method, a multi-layer feedforward neural network based on error reverse propagation, namely a BP neural network, is utilized to construct an estimation model of the carbon-nitrogen ratio of the oil-tea camellia leaves and the visible light and near-infrared spectrum region hyperspectrum, and the measured canopy hyperspectrum of the oil-tea camellia to be measured is input into the estimation model to obtain the carbon-nitrogen ratio data of the oil-tea camellia leaves to be measured. According to the invention, the BP neural network algorithm is adopted to train and learn the carbon-nitrogen ratio of the tea-oil tree leaf and the hyperspectral characteristics of the canopy, potential hyperspectral response characteristics influencing the estimation of the carbon-nitrogen ratio of |
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According to the method, a multi-layer feedforward neural network based on error reverse propagation, namely a BP neural network, is utilized to construct an estimation model of the carbon-nitrogen ratio of the oil-tea camellia leaves and the visible light and near-infrared spectrum region hyperspectrum, and the measured canopy hyperspectrum of the oil-tea camellia to be measured is input into the estimation model to obtain the carbon-nitrogen ratio data of the oil-tea camellia leaves to be measured. According to the invention, the BP neural network algorithm is adopted to train and learn the carbon-nitrogen ratio of the tea-oil tree leaf and the hyperspectral characteristics of the canopy, potential hyperspectral response characteristics influencing the estimation of the carbon-nitrogen ratio of</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES ; MEASURING ; PHYSICS ; TESTING</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230314&DB=EPODOC&CC=CN&NR=115791705A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230314&DB=EPODOC&CC=CN&NR=115791705A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>YAN LIPENG</creatorcontrib><creatorcontrib>DOU MIN</creatorcontrib><creatorcontrib>TANG XUEHAI</creatorcontrib><creatorcontrib>HUANG QINGFENG</creatorcontrib><creatorcontrib>GAO XIANG</creatorcontrib><creatorcontrib>WANG AQING</creatorcontrib><creatorcontrib>KUANG FAN</creatorcontrib><creatorcontrib>QIAN WENQI</creatorcontrib><creatorcontrib>FU GENSHEN</creatorcontrib><creatorcontrib>XU CHENG</creatorcontrib><title>Camellia oleifera leaf carbon nitrogen ratio estimation method based on canopy hyperspectrum</title><description>The invention relates to the technical field of oil-tea camellia leaf carbon-nitrogen ratio estimation, in particular to an oil-tea camellia leaf carbon-nitrogen ratio estimation method based on canopy hyperspectrum. 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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES MEASURING PHYSICS TESTING |
| title | Camellia oleifera leaf carbon nitrogen ratio estimation method based on canopy hyperspectrum |
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