Neural network-based cyperus esculentus oil content near-infrared analysis model and characteristic wavelength extraction method
The invention relates to a near-infrared model establishment method and a characteristic wavelength extraction method for predicting the oil content of cyperus esculentus, and belongs to the field of near-infrared spectrum analysis. According to the method, the MLP neural network is combined with PL...
Gespeichert in:
| Hauptverfasser: | , , , , , , , , , , , , |
|---|---|
| Format: | Patent |
| Sprache: | chi ; eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | WANG YING MIMA DUNZHU SHI XUESHUANG ZHANG BIN LI CHANGJIE DAWA ZHUOMA ZHAO QIAN ZHAO JIANGTAO DANG XIQIANG CHILIETZOOM LAM WEI HAIFENG GAO WENWEI |
| description | The invention relates to a near-infrared model establishment method and a characteristic wavelength extraction method for predicting the oil content of cyperus esculentus, and belongs to the field of near-infrared spectrum analysis. According to the method, the MLP neural network is combined with PLS cross validation, the characteristic wavelength related to the oil content in the near infrared spectrum of the cyperus esculentus is extracted, the screened characteristic near infrared information related to the oil content is used for fitting with the oil content, the accuracy of the obtained near infrared model is better, the predictive capacity is greatly improved, and meanwhile the number of the characteristic wavelength is smaller. By utilizing the established near-infrared analysis model, the oil content of the cyperus esculentus can be predicted only by measuring the near-infrared spectrum information of the cyperus esculentus, and rapid, nondestructive and accurate measurement is realized.
本发明涉及一种预测油莎豆含 |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN117854617A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN117854617A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN117854617A3</originalsourceid><addsrcrecordid>eNqNjj0OwjAMRrswIOAO5gAdKn7KiioQUyf2yqQujUiTynYp3Tg6QeIATP6evmfL8-Rd0sDowJOOgR_pDYVqMFNPPAiQmMGR1xiDdWCC10hRRk6tbxg5yujRTWIFulCTixj3W2Q0SmxFrYERnxTP3LUFeum3scFDR9qGepnMGnRCq99cJOvz6VpcUupDRdKjofhbVZRZlh92232WHzf_OB8RqkrP</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Neural network-based cyperus esculentus oil content near-infrared analysis model and characteristic wavelength extraction method</title><source>esp@cenet</source><creator>WANG YING ; MIMA DUNZHU ; SHI XUESHUANG ; ZHANG BIN ; LI CHANGJIE ; DAWA ZHUOMA ; ZHAO QIAN ; ZHAO JIANGTAO ; DANG XIQIANG ; CHILIETZOOM ; LAM ; WEI HAIFENG ; GAO WENWEI</creator><creatorcontrib>WANG YING ; MIMA DUNZHU ; SHI XUESHUANG ; ZHANG BIN ; LI CHANGJIE ; DAWA ZHUOMA ; ZHAO QIAN ; ZHAO JIANGTAO ; DANG XIQIANG ; CHILIETZOOM ; LAM ; WEI HAIFENG ; GAO WENWEI</creatorcontrib><description>The invention relates to a near-infrared model establishment method and a characteristic wavelength extraction method for predicting the oil content of cyperus esculentus, and belongs to the field of near-infrared spectrum analysis. According to the method, the MLP neural network is combined with PLS cross validation, the characteristic wavelength related to the oil content in the near infrared spectrum of the cyperus esculentus is extracted, the screened characteristic near infrared information related to the oil content is used for fitting with the oil content, the accuracy of the obtained near infrared model is better, the predictive capacity is greatly improved, and meanwhile the number of the characteristic wavelength is smaller. By utilizing the established near-infrared analysis model, the oil content of the cyperus esculentus can be predicted only by measuring the near-infrared spectrum information of the cyperus esculentus, and rapid, nondestructive and accurate measurement is realized.
本发明涉及一种预测油莎豆含</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES ; MEASURING ; PHYSICS ; TESTING</subject><creationdate>2024</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=20240409&DB=EPODOC&CC=CN&NR=117854617A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,777,882,25545,76296</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240409&DB=EPODOC&CC=CN&NR=117854617A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG YING</creatorcontrib><creatorcontrib>MIMA DUNZHU</creatorcontrib><creatorcontrib>SHI XUESHUANG</creatorcontrib><creatorcontrib>ZHANG BIN</creatorcontrib><creatorcontrib>LI CHANGJIE</creatorcontrib><creatorcontrib>DAWA ZHUOMA</creatorcontrib><creatorcontrib>ZHAO QIAN</creatorcontrib><creatorcontrib>ZHAO JIANGTAO</creatorcontrib><creatorcontrib>DANG XIQIANG</creatorcontrib><creatorcontrib>CHILIETZOOM</creatorcontrib><creatorcontrib>LAM</creatorcontrib><creatorcontrib>WEI HAIFENG</creatorcontrib><creatorcontrib>GAO WENWEI</creatorcontrib><title>Neural network-based cyperus esculentus oil content near-infrared analysis model and characteristic wavelength extraction method</title><description>The invention relates to a near-infrared model establishment method and a characteristic wavelength extraction method for predicting the oil content of cyperus esculentus, and belongs to the field of near-infrared spectrum analysis. According to the method, the MLP neural network is combined with PLS cross validation, the characteristic wavelength related to the oil content in the near infrared spectrum of the cyperus esculentus is extracted, the screened characteristic near infrared information related to the oil content is used for fitting with the oil content, the accuracy of the obtained near infrared model is better, the predictive capacity is greatly improved, and meanwhile the number of the characteristic wavelength is smaller. By utilizing the established near-infrared analysis model, the oil content of the cyperus esculentus can be predicted only by measuring the near-infrared spectrum information of the cyperus esculentus, and rapid, nondestructive and accurate measurement is realized.
本发明涉及一种预测油莎豆含</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</subject><subject>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNjj0OwjAMRrswIOAO5gAdKn7KiioQUyf2yqQujUiTynYp3Tg6QeIATP6evmfL8-Rd0sDowJOOgR_pDYVqMFNPPAiQmMGR1xiDdWCC10hRRk6tbxg5yujRTWIFulCTixj3W2Q0SmxFrYERnxTP3LUFeum3scFDR9qGepnMGnRCq99cJOvz6VpcUupDRdKjofhbVZRZlh92232WHzf_OB8RqkrP</recordid><startdate>20240409</startdate><enddate>20240409</enddate><creator>WANG YING</creator><creator>MIMA DUNZHU</creator><creator>SHI XUESHUANG</creator><creator>ZHANG BIN</creator><creator>LI CHANGJIE</creator><creator>DAWA ZHUOMA</creator><creator>ZHAO QIAN</creator><creator>ZHAO JIANGTAO</creator><creator>DANG XIQIANG</creator><creator>CHILIETZOOM</creator><creator>LAM</creator><creator>WEI HAIFENG</creator><creator>GAO WENWEI</creator><scope>EVB</scope></search><sort><creationdate>20240409</creationdate><title>Neural network-based cyperus esculentus oil content near-infrared analysis model and characteristic wavelength extraction method</title><author>WANG YING ; MIMA DUNZHU ; SHI XUESHUANG ; ZHANG BIN ; LI CHANGJIE ; DAWA ZHUOMA ; ZHAO QIAN ; ZHAO JIANGTAO ; DANG XIQIANG ; CHILIETZOOM ; LAM ; WEI HAIFENG ; GAO WENWEI</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117854617A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</topic><topic>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>WANG YING</creatorcontrib><creatorcontrib>MIMA DUNZHU</creatorcontrib><creatorcontrib>SHI XUESHUANG</creatorcontrib><creatorcontrib>ZHANG BIN</creatorcontrib><creatorcontrib>LI CHANGJIE</creatorcontrib><creatorcontrib>DAWA ZHUOMA</creatorcontrib><creatorcontrib>ZHAO QIAN</creatorcontrib><creatorcontrib>ZHAO JIANGTAO</creatorcontrib><creatorcontrib>DANG XIQIANG</creatorcontrib><creatorcontrib>CHILIETZOOM</creatorcontrib><creatorcontrib>LAM</creatorcontrib><creatorcontrib>WEI HAIFENG</creatorcontrib><creatorcontrib>GAO WENWEI</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WANG YING</au><au>MIMA DUNZHU</au><au>SHI XUESHUANG</au><au>ZHANG BIN</au><au>LI CHANGJIE</au><au>DAWA ZHUOMA</au><au>ZHAO QIAN</au><au>ZHAO JIANGTAO</au><au>DANG XIQIANG</au><au>CHILIETZOOM</au><au>LAM</au><au>WEI HAIFENG</au><au>GAO WENWEI</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Neural network-based cyperus esculentus oil content near-infrared analysis model and characteristic wavelength extraction method</title><date>2024-04-09</date><risdate>2024</risdate><abstract>The invention relates to a near-infrared model establishment method and a characteristic wavelength extraction method for predicting the oil content of cyperus esculentus, and belongs to the field of near-infrared spectrum analysis. According to the method, the MLP neural network is combined with PLS cross validation, the characteristic wavelength related to the oil content in the near infrared spectrum of the cyperus esculentus is extracted, the screened characteristic near infrared information related to the oil content is used for fitting with the oil content, the accuracy of the obtained near infrared model is better, the predictive capacity is greatly improved, and meanwhile the number of the characteristic wavelength is smaller. By utilizing the established near-infrared analysis model, the oil content of the cyperus esculentus can be predicted only by measuring the near-infrared spectrum information of the cyperus esculentus, and rapid, nondestructive and accurate measurement is realized.
本发明涉及一种预测油莎豆含</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN117854617A |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES MEASURING PHYSICS TESTING |
| title | Neural network-based cyperus esculentus oil content near-infrared analysis model and characteristic wavelength extraction method |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T02%3A52%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=WANG%20YING&rft.date=2024-04-09&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN117854617A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |