{"id":"https://openalex.org/W2057471384","doi":"https://doi.org/10.4304/jcp.9.1.228-234","title":"An Objective Wavelength Selection Method Based on Moving Window Partial Least Squares for Near-Infrared Spectroscopy","display_name":"An Objective Wavelength Selection Method Based on Moving Window Partial Least Squares for Near-Infrared Spectroscopy","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2057471384","doi":"https://doi.org/10.4304/jcp.9.1.228-234","mag":"2057471384"},"language":"en","primary_location":{"id":"doi:10.4304/jcp.9.1.228-234","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jcp.9.1.228-234","pdf_url":null,"source":{"id":"https://openalex.org/S77894049","display_name":"Journal of Computers","issn_l":"1796-203X","issn":["1796-203X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computers","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100562164","display_name":"Long Xu","orcid":"https://orcid.org/0000-0002-7801-4627"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Long Xu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017135163","display_name":"Jiangang Lu","orcid":"https://orcid.org/0000-0002-1551-6179"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiangang Lu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062534500","display_name":"Qinmin Yang","orcid":"https://orcid.org/0000-0002-1602-8986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qinmin Yang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007848429","display_name":"Jinshui Chen","orcid":"https://orcid.org/0000-0002-8588-3345"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinshui Chen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Yingzi Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yingzi Shi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100562164"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.09067597,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"9","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.6300998330116272},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.6138468384742737},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6102373003959656},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.5594752430915833},{"id":"https://openalex.org/keywords/wavelength","display_name":"Wavelength","score":0.5286415219306946},{"id":"https://openalex.org/keywords/spectroscopy","display_name":"Spectroscopy","score":0.5193427801132202},{"id":"https://openalex.org/keywords/infrared-spectroscopy","display_name":"Infrared spectroscopy","score":0.46824729442596436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40996456146240234},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.34839484095573425},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.3326954245567322},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3131793141365051},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.23434248566627502},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22012266516685486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1959388256072998}],"concepts":[{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.6300998330116272},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.6138468384742737},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6102373003959656},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.5594752430915833},{"id":"https://openalex.org/C6260449","wikidata":"https://www.wikidata.org/wiki/Q41364","display_name":"Wavelength","level":2,"score":0.5286415219306946},{"id":"https://openalex.org/C32891209","wikidata":"https://www.wikidata.org/wiki/Q483666","display_name":"Spectroscopy","level":2,"score":0.5193427801132202},{"id":"https://openalex.org/C153642686","wikidata":"https://www.wikidata.org/wiki/Q70906","display_name":"Infrared spectroscopy","level":2,"score":0.46824729442596436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40996456146240234},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.34839484095573425},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.3326954245567322},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3131793141365051},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.23434248566627502},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22012266516685486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1959388256072998},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4304/jcp.9.1.228-234","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jcp.9.1.228-234","pdf_url":null,"source":{"id":"https://openalex.org/S77894049","display_name":"Journal of Computers","issn_l":"1796-203X","issn":["1796-203X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1967083058","https://openalex.org/W1970542683","https://openalex.org/W1971529025","https://openalex.org/W1973087775","https://openalex.org/W1980033015","https://openalex.org/W1982230615","https://openalex.org/W1982755765","https://openalex.org/W2007808016","https://openalex.org/W2009552254","https://openalex.org/W2012204449","https://openalex.org/W2021754455","https://openalex.org/W2024312162","https://openalex.org/W2030753670","https://openalex.org/W2036804696","https://openalex.org/W2043689097","https://openalex.org/W2050605378","https://openalex.org/W2084169316","https://openalex.org/W2124972294"],"related_works":["https://openalex.org/W2135375667","https://openalex.org/W4323652357","https://openalex.org/W2008512696","https://openalex.org/W4236933654","https://openalex.org/W2916853706","https://openalex.org/W2490963019","https://openalex.org/W2018674345","https://openalex.org/W2469340274","https://openalex.org/W117824151","https://openalex.org/W1982027788"],"abstract_inverted_index":{"An":[0],"objective":[1,110],"wavelength":[2,38,66,141],"selection":[3,142],"method":[4],"is":[5],"proposed":[6],"for":[7],"near-infrared":[8,148],"(NIR)":[9],"spectroscopy":[10],"mainly":[11],"to":[12,33,79,114],"overcome":[13],"the":[14,49,52,94,103,121,130],"possible":[15],"subjectivity":[16],"introduced":[17,30],"by":[18,45,62,88],"moving":[19],"window":[20],"partial":[21],"least":[22],"squares":[23],"regression":[24],"(MWPLS).":[25],"This":[26],"improved":[27],"procedure":[28,111],"(iMWPLS)":[29],"an":[31,139],"indicator":[32,53],"evaluate":[34],"importance":[35],"of":[36,51,57,84],"each":[37,89],"and":[39,67,120,129,143],"then":[40],"all":[41,73],"wavelengths":[42,74,91],"were":[43,60,75,97,105],"ranked":[44],"these":[46],"indicators.":[47],"On":[48],"basis":[50],"ranking,":[54],"a":[55,69],"series":[56],"PLS":[58,128],"models":[59],"constructed":[61,93],"starting":[63],"with":[64,126],"one":[65,71],"incorporating":[68],"new":[70,109],"until":[72],"involved.":[76],"Finally,":[77],"according":[78],"root":[80],"mean":[81],"square":[82],"error":[83],"cross-validation":[85],"(RMSECV)":[86],"obtained":[87],"model,":[90],"that":[92,135],"optimal":[95],"model":[96],"selected":[98],"as":[99],"informative":[100],"ones":[101],"while":[102],"others":[104],"discarded.":[106],"Subsequently,":[107],"this":[108],"was":[112,124],"applied":[113],"two":[115],"real":[116],"standard":[117],"NIR":[118],"datasets":[119],"prediction":[122],"performance":[123],"compared":[125],"full-spectrum":[127],"original":[131],"MWPLS.":[132],"Results":[133],"demonstrated":[134],"iMWPLS":[136],"could":[137],"achieve":[138],"effective":[140],"improve":[144],"predictive":[145],"accuracy":[146],"in":[147],"spectroscopy.":[149]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}