{"id":"https://openalex.org/W4391496231","doi":"https://doi.org/10.1109/m2vip58386.2023.10413390","title":"Quality Prediction of PECVD Process with Random Forest and Long Short-Term Memory Neural Network","display_name":"Quality Prediction of PECVD Process with Random Forest and Long Short-Term Memory Neural Network","publication_year":2023,"publication_date":"2023-11-21","ids":{"openalex":"https://openalex.org/W4391496231","doi":"https://doi.org/10.1109/m2vip58386.2023.10413390"},"language":"en","primary_location":{"id":"doi:10.1109/m2vip58386.2023.10413390","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/m2vip58386.2023.10413390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5038887133","display_name":"Yilei Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilei Fu","raw_affiliation_strings":["School of Mechanical Engineering, Southeast University,Nanjing,China","School of Mechanical Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100643311","display_name":"Zhisheng Zhang","orcid":"https://orcid.org/0000-0002-8084-6270"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhisheng Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Southeast University,Nanjing,China","School of Mechanical Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033942539","display_name":"Zhijie Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhijie Xia","raw_affiliation_strings":["JiangSu Nan Gao Intelligent Equipment Innovation Center,Nanjing,China","JiangSu Nan Gao Intelligent Equipment Innovation Center, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JiangSu Nan Gao Intelligent Equipment Innovation Center,Nanjing,China","institution_ids":[]},{"raw_affiliation_string":"JiangSu Nan Gao Intelligent Equipment Innovation Center, Nanjing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025970821","display_name":"Haiying Wen","orcid":"https://orcid.org/0000-0001-7096-7581"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiying Wen","raw_affiliation_strings":["School of Mechanical Engineering Southeast University, Engineering Research Center of New Light Sources Technology and Equipment, Ministry of Education,Nanjing,China","School of Mechanical Engineering Southeast University, Engineering Research Center of New Light Sources Technology and Equipment, Ministry of Education, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering Southeast University, Engineering Research Center of New Light Sources Technology and Equipment, Ministry of Education,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mechanical Engineering Southeast University, Engineering Research Center of New Light Sources Technology and Equipment, Ministry of Education, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112121793","display_name":"Min Dai","orcid":"https://orcid.org/0000-0002-1301-7982"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Dai","raw_affiliation_strings":["School of Mechanical Engineering, Southeast University,Nanjing,China","School of Mechanical Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100323420","display_name":"Hui Zhang","orcid":"https://orcid.org/0000-0002-1803-3148"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Southeast University,Nanjing,China","School of Mechanical Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9314000010490417,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9314000010490417,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9279000163078308,"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/T10461","display_name":"Gas Sensing Nanomaterials and Sensors","score":0.9063000082969666,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.6861340999603271},{"id":"https://openalex.org/keywords/plasma-enhanced-chemical-vapor-deposition","display_name":"Plasma-enhanced chemical vapor deposition","score":0.6726371049880981},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5940322875976562},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5776317119598389},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5446987152099609},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.49297547340393066},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34668147563934326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33400410413742065},{"id":"https://openalex.org/keywords/chemical-vapor-deposition","display_name":"Chemical vapor deposition","score":0.17621099948883057},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1361415684223175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6861340999603271},{"id":"https://openalex.org/C38347018","wikidata":"https://www.wikidata.org/wiki/Q905958","display_name":"Plasma-enhanced chemical vapor deposition","level":3,"score":0.6726371049880981},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5940322875976562},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5776317119598389},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5446987152099609},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.49297547340393066},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34668147563934326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33400410413742065},{"id":"https://openalex.org/C57410435","wikidata":"https://www.wikidata.org/wiki/Q505668","display_name":"Chemical vapor deposition","level":2,"score":0.17621099948883057},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1361415684223175},{"id":"https://openalex.org/C49040817","wikidata":"https://www.wikidata.org/wiki/Q193091","display_name":"Optoelectronics","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},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/m2vip58386.2023.10413390","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/m2vip58386.2023.10413390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G5272672812","display_name":null,"funder_award_id":"51775108","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1976778365","https://openalex.org/W1988338159","https://openalex.org/W2050323089","https://openalex.org/W2760466876","https://openalex.org/W2967372777","https://openalex.org/W2992148407","https://openalex.org/W3002283813","https://openalex.org/W3082584658","https://openalex.org/W3157654875","https://openalex.org/W3161577134","https://openalex.org/W3175291036","https://openalex.org/W3181448069","https://openalex.org/W4210446036","https://openalex.org/W4304182802","https://openalex.org/W4375858565"],"related_works":["https://openalex.org/W2124081025","https://openalex.org/W1963703370","https://openalex.org/W2315275742","https://openalex.org/W142624727","https://openalex.org/W2026758251","https://openalex.org/W3193043704","https://openalex.org/W2081807968","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305"],"abstract_inverted_index":{"Plasma":[0],"enhanced":[1],"chemical":[2],"vapor":[3],"deposition":[4],"(PECVD)":[5],"is":[6,39,122],"a":[7,80],"key":[8],"process":[9,38,98],"for":[10,19,166],"producing":[11],"the":[12,24,35,56,59,68,72,75,94,97,101,117,129,134,145,148,173,176,184],"surface":[13],"thin":[14],"film":[15],"of":[16,30,83,119,133,147],"high-energy":[17],"batteries":[18],"that":[20,152,172],"it":[21],"could":[22],"enhance":[23],"absorption":[25],"and":[26,45,78,86,100,128],"energy":[27],"conversion":[28],"rates":[29],"solar":[31],"cell":[32],"films.":[33],"While":[34],"PECVD":[36,110],"coating":[37],"complex":[40],"enough":[41,165],"to":[42,49,92],"be":[43],"realized":[44],"requires":[46],"various":[47],"sensors":[48,108],"collect":[50],"data":[51,104,121,135],"as":[52,54],"well":[53],"monitor":[55],"quality":[57,102],"throughout":[58],"process.":[60,111],"This":[61],"paper":[62],"first":[63],"performs":[64],"correlation":[65],"analysis":[66],"on":[67],"collected":[69,105],"data,":[70,77],"examines":[71],"relationship":[73,95],"between":[74,96],"multi-sensor":[76,120],"proposes":[79],"hybrid":[81,114],"algorithm":[82,115,150],"random":[84,125],"forest":[85,126],"long":[87],"short-term":[88],"memory":[89],"network":[90],"(LSTM)":[91],"predict":[93],"parameters":[99,103],"by":[106,124,138,179],"multiple":[107],"in":[109],"In":[112],"this":[113],"model,":[116],"importance":[118],"extracted":[123],"module,":[127],"time":[130],"series":[131],"features":[132,157],"are":[136,162],"analyzed":[137],"LSTM.":[139],"The":[140,169],"proposed":[141],"novel":[142],"method":[143],"overcomes":[144],"limitations":[146],"existing":[149],"models":[151],"only":[153],"consider":[154],"either":[155],"temporal":[156],"or":[158],"important":[159],"features,":[160],"which":[161],"not":[163],"comprehensive":[164],"practical":[167],"applications.":[168],"result":[170],"reveals":[171],"RF-LSTM":[174],"improves":[175],"prediction":[177],"accuracy":[178],"40%":[180],"without":[181],"significantly":[182],"increasing":[183],"iteration":[185],"time.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
