{"id":"https://openalex.org/W7118874484","doi":"https://doi.org/10.1109/indin64977.2025.11279020","title":"Graph Feature Learning-Based Virtual Sample Generation and Sample-weighted Soft Sensor Method","display_name":"Graph Feature Learning-Based Virtual Sample Generation and Sample-weighted Soft Sensor Method","publication_year":2025,"publication_date":"2025-07-12","ids":{"openalex":"https://openalex.org/W7118874484","doi":"https://doi.org/10.1109/indin64977.2025.11279020"},"language":null,"primary_location":{"id":"doi:10.1109/indin64977.2025.11279020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin64977.2025.11279020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 23rd International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-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/A5122064002","display_name":"Zhiheng Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Jiang","raw_affiliation_strings":["Kunming University of Science and Technology,School of Information Engineering and Automation,Kunming,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology,School of Information Engineering and Automation,Kunming,China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372433","display_name":"Bin Wang","orcid":"https://orcid.org/0009-0001-7917-9327"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wang","raw_affiliation_strings":["Kunming University of Science and Technology,School of Information Engineering and Automation,Kunming,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology,School of Information Engineering and Automation,Kunming,China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101298009","display_name":"Wangyang Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155232","display_name":"Fiberhome Technology Group (China)","ror":"https://ror.org/04yv20134","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210155232"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wangyang Yu","raw_affiliation_strings":["Wuhan Maritime Communication Research Institute,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan Maritime Communication Research Institute,Wuhan,China","institution_ids":["https://openalex.org/I4210155232"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5120975869","display_name":"Huaiping Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaiping Jin","raw_affiliation_strings":["Kunming University of Science and Technology,School of Information Engineering and Automation,Kunming,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kunming University of Science and Technology,School of Information Engineering and Automation,Kunming,China","institution_ids":["https://openalex.org/I10660446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.5868949,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.8454999923706055,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.8454999923706055,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.04639999940991402,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10763","display_name":"Digital Transformation in Industry","score":0.00839999970048666,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/soft-sensor","display_name":"Soft sensor","score":0.6764000058174133},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5234000086784363},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5139999985694885},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.46959999203681946},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4390000104904175},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4262000024318695},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4198000133037567},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.41670000553131104}],"concepts":[{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.6764000058174133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6654000282287598},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5234000086784363},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5145000219345093},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5139999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48590001463890076},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.46959999203681946},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.41670000553131104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40139999985694885},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.34279999136924744},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C140073362","wikidata":"https://www.wikidata.org/wiki/Q738759","display_name":"Soft computing","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/indin64977.2025.11279020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin64977.2025.11279020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 23rd International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6819591522216797,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2765946341","https://openalex.org/W2901504064","https://openalex.org/W2979389376","https://openalex.org/W3096831136","https://openalex.org/W3177624059","https://openalex.org/W3189164715","https://openalex.org/W4206713150","https://openalex.org/W4292805591","https://openalex.org/W4293519360","https://openalex.org/W4297896097","https://openalex.org/W4310837319","https://openalex.org/W4313201409","https://openalex.org/W4313479464","https://openalex.org/W4366112286","https://openalex.org/W4366245308","https://openalex.org/W4382998922","https://openalex.org/W4387587589"],"related_works":[],"abstract_inverted_index":{"In":[0],"complex":[1],"industrial":[2,199],"processes,":[3],"digital":[4],"twin":[5],"technology":[6],"faces":[7],"modeling":[8,124],"difficulties":[9,52],"due":[10,29,50],"to":[11,30,51,76,132,135,158,175,178],"the":[12,84,93,137,156,163,185,192],"absence":[13],"of":[14,33,92,95,165,191],"key":[15],"quality":[16,27,94],"variables,":[17],"data":[18,40,48,59,117],"driven":[19,41],"soft":[20,42,122,186],"sensing":[21,43,123,187],"demonstrates":[22],"significant":[23],"potential":[24],"in":[25,53,63,99,103,184],"predicting":[26],"variables":[28],"its":[31],"advantages":[32],"low":[34],"cost":[35],"and":[36,57,88,119,167],"rapid":[37],"response.":[38],"However,":[39],"models":[44],"often":[45],"suffer":[46],"from":[47],"scarcity":[49],"obtaining":[54],"labeled":[55],"samples":[56,101,142,180],"high":[58],"repetition":[60],"rates,":[61],"which":[62],"turn":[64],"affects":[65],"prediction":[66],"accuracy.":[67],"Although":[68],"virtual":[69,179],"sample":[70,120,171],"generation":[71],"methods":[72,81],"have":[73],"been":[74],"proposed":[75,115,193],"alleviate":[77],"this":[78,113],"issue,":[79],"existing":[80],"generally":[82],"overlook":[83],"interdependencies":[85,161],"among":[86],"features":[87,164],"lack":[89],"effective":[90],"evaluation":[91],"generated":[96,166],"samples,":[97],"resulting":[98],"all":[100],"participating":[102],"model":[104,144,147],"training":[105],"with":[106],"equal":[107],"weights.":[108],"To":[109],"address":[110],"these":[111],"shortcomings,":[112],"paper":[114],"a":[116,149],"augmentation":[118],"weighting":[121],"method":[125,194],"based":[126],"on":[127,143],"graph":[128],"feature":[129],"learning,":[130],"referred":[131],"as":[133],"GFSW-VSG,":[134],"mitigate":[136],"constraints":[138],"imposed":[139],"by":[140],"insufficient":[141],"performance.":[145],"This":[146],"introduces":[148],"Graph":[150],"Convolutional":[151],"Neural":[152],"Network":[153],"(GCN)":[154],"into":[155],"discriminator":[157],"maintain":[159],"consistent":[160],"between":[162],"original":[168],"data.":[169],"Subsequently,":[170],"confidence":[172],"is":[173,195],"calculated":[174],"assign":[176],"weights":[177],"for":[181],"weighted":[182],"learning":[183],"model.":[188],"The":[189],"effectiveness":[190],"validated":[196],"through":[197],"an":[198],"chlortetracycline":[200],"(CTC)":[201],"fermentation":[202],"process.":[203]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-08T00:00:00"}
