{"id":"https://openalex.org/W3097756811","doi":"https://doi.org/10.1109/access.2020.3036006","title":"Control Chart Patterns Recognition Based on Optimized Deep Belief Neural Network and Data Information Enhancement","display_name":"Control Chart Patterns Recognition Based on Optimized Deep Belief Neural Network and Data Information Enhancement","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3097756811","doi":"https://doi.org/10.1109/access.2020.3036006","mag":"3097756811"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3036006","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036006","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09248993.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09248993.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100743712","display_name":"Hongyan Chu","orcid":"https://orcid.org/0000-0002-0120-4270"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]},{"id":"https://openalex.org/I4210157608","display_name":"Institute of Advanced Manufacturing Technology","ror":"https://ror.org/05egxdg81","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210157608"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Chu","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China","Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210157608"]},{"raw_affiliation_string":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010351288","display_name":"Kailin Zhao","orcid":"https://orcid.org/0000-0003-0208-0174"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]},{"id":"https://openalex.org/I4210157608","display_name":"Institute of Advanced Manufacturing Technology","ror":"https://ror.org/05egxdg81","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210157608"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kailin Zhao","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China","Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0208-0174","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210157608"]},{"raw_affiliation_string":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767866","display_name":"Qiang Cheng","orcid":"https://orcid.org/0000-0001-5446-3658"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]},{"id":"https://openalex.org/I4210157608","display_name":"Institute of Advanced Manufacturing Technology","ror":"https://ror.org/05egxdg81","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210157608"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Cheng","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China","Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5446-3658","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210157608"]},{"raw_affiliation_string":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448538","display_name":"Rui Li","orcid":"https://orcid.org/0000-0002-7648-7148"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Li","raw_affiliation_strings":["Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China","Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]},{"raw_affiliation_string":"Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073910119","display_name":"Congbin Yang","orcid":"https://orcid.org/0000-0003-1040-6840"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Congbin Yang","raw_affiliation_strings":["Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China","Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1040-6840","affiliations":[{"raw_affiliation_string":"Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]},{"raw_affiliation_string":"Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.4895,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7280713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"203685","last_page":"203699"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9882000088691711,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9783999919891357,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7991845607757568},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.650611162185669},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5998377203941345},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.578569769859314},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.5663602948188782},{"id":"https://openalex.org/keywords/control-chart","display_name":"Control chart","score":0.5603160858154297},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5257701873779297},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5202573537826538},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5169381499290466},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47767525911331177},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.47348248958587646},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.44374001026153564},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3665476441383362}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7991845607757568},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.650611162185669},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5998377203941345},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.578569769859314},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.5663602948188782},{"id":"https://openalex.org/C196985124","wikidata":"https://www.wikidata.org/wiki/Q1369242","display_name":"Control chart","level":3,"score":0.5603160858154297},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5257701873779297},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5202573537826538},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5169381499290466},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47767525911331177},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.47348248958587646},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.44374001026153564},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3665476441383362},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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":2,"locations":[{"id":"doi:10.1109/access.2020.3036006","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036006","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09248993.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7c7bfb02ab8e48ee87084f21fca551ab","is_oa":true,"landing_page_url":"https://doaj.org/article/7c7bfb02ab8e48ee87084f21fca551ab","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 203685-203699 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3036006","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036006","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09248993.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1427204724","display_name":null,"funder_award_id":"2019ZX04024001","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"},{"id":"https://openalex.org/G1655051861","display_name":null,"funder_award_id":"Z191100001119010","funder_id":"https://openalex.org/F4320326444","funder_display_name":"Nova"},{"id":"https://openalex.org/G3378616741","display_name":null,"funder_award_id":"51975012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326444","display_name":"Nova","ror":null},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W277331452","https://openalex.org/W1968732018","https://openalex.org/W1970331804","https://openalex.org/W1975777064","https://openalex.org/W1998994572","https://openalex.org/W2015974984","https://openalex.org/W2017018726","https://openalex.org/W2024962697","https://openalex.org/W2030242308","https://openalex.org/W2038585870","https://openalex.org/W2042528732","https://openalex.org/W2044036264","https://openalex.org/W2049597952","https://openalex.org/W2051745706","https://openalex.org/W2053157736","https://openalex.org/W2065953269","https://openalex.org/W2068083201","https://openalex.org/W2091311817","https://openalex.org/W2094544771","https://openalex.org/W2101178528","https://openalex.org/W2111146558","https://openalex.org/W2132706350","https://openalex.org/W2148364730","https://openalex.org/W2169133682","https://openalex.org/W2278165553","https://openalex.org/W2345852405","https://openalex.org/W2612554669","https://openalex.org/W2791282478","https://openalex.org/W2793445666","https://openalex.org/W2799400737","https://openalex.org/W2800297739","https://openalex.org/W2859065224","https://openalex.org/W2889385573","https://openalex.org/W2960015156","https://openalex.org/W2969034172","https://openalex.org/W2972431882","https://openalex.org/W2979048634","https://openalex.org/W2995860668","https://openalex.org/W2996236378","https://openalex.org/W3015801892","https://openalex.org/W3016701685","https://openalex.org/W3071892017","https://openalex.org/W4245276699","https://openalex.org/W6753194791"],"related_works":["https://openalex.org/W2064630666","https://openalex.org/W1974618110","https://openalex.org/W2287713958","https://openalex.org/W1257380361","https://openalex.org/W2133034788","https://openalex.org/W3005559199","https://openalex.org/W2402196265","https://openalex.org/W3135656750","https://openalex.org/W2513801676","https://openalex.org/W3121598771"],"abstract_inverted_index":{"Control":[0],"chart":[1],"patterns":[2,19],"(CCPs)":[3],"are":[4,36],"often":[5],"used":[6,37,101],"for":[7,230],"quality":[8],"control":[9],"in":[10,121,214],"the":[11,25,29,43,46,61,69,104,114,119,125,134,139,159,173,180,194,211,221],"manufacturing":[12],"process,":[13,28],"and":[14,32,55,74,87,96,108,128,177,186,191,220],"effective":[15],"recognition":[16,78,222],"of":[17,34,48,53,63,71,167,179,233],"these":[18,110],"is":[20],"critical":[21],"to":[22,38,60,67,102,117,123,137,171],"manufacturing.":[23],"In":[24,65],"dynamic":[26],"production":[27],"raw":[30,115],"data":[31,88,116,126,132,140,175],"features":[33,94,107,111,136],"CCPs":[35,49,77],"recognize":[39],"or":[40],"further":[41],"predict":[42],"trends.":[44],"However,":[45],"inaccuracy":[47],"information":[50,72,89,97],"extraction,":[51],"loss":[52],"information,":[54],"complex":[56],"recognizer":[57],"can":[58],"lead":[59],"difficulty":[62],"recognition.":[64],"order":[66,122],"improve":[68],"accuracy":[70,223],"extraction":[73],"recognition,":[75],"a":[76,146],"method":[79,166,198,212,227],"based":[80,188],"on":[81,189],"optimized":[82,156],"deep":[83],"belief":[84],"network":[85,181],"(DBN)":[86],"enhancement":[90,98],"was":[91,100,155,169,199,228],"proposed.":[92],"Adaptive":[93],"selection":[95],"(AFIE)":[99],"select":[103],"most":[105],"appropriate":[106],"make":[109],"combine":[112,130],"with":[113,133,148,201],"from":[118],"dataset":[120],"reduce":[124],"dimension,":[127],"then":[129],"dimensioned":[131],"selected":[135],"enhance":[138],"information.":[141],"Further,":[142],"this":[143,197,215,226],"study":[144,216],"presented":[145],"DBN":[147],"three":[149],"restricted":[150],"Boltzmann":[151],"machine":[152],"structures,":[153],"which":[154],"by":[157,225],"using":[158],"artificial":[160],"fish":[161],"swarm":[162],"algorithm":[163],"(AFSA).":[164],"The":[165,206],"AFIE":[168],"discussed":[170,187],"obtain":[172],"optimal":[174],"set,":[176],"parameters":[178],"structure":[182],"were":[183],"analyzed,":[184],"optimized,":[185],"experiments":[190],"AFSA.":[192],"At":[193],"same":[195],"time,":[196],"compared":[200],"multi-layer":[202],"perceptron":[203],"neural":[204],"network.":[205],"simulation":[207],"results":[208],"showed":[209],"that":[210],"proposed":[213],"exhibited":[217],"excellent":[218],"effect,":[219],"achieved":[224],"99.78%":[229],"2000":[231],"samples":[232],"each":[234],"pattern.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}