{"id":"https://openalex.org/W2904750179","doi":"https://doi.org/10.1109/access.2018.2886820","title":"Mutual Information-Weighted Principle Components Identified From the Depth Features of Stacked Autoencoders and Original Variables for Oil Dry Point Soft Sensor","display_name":"Mutual Information-Weighted Principle Components Identified From the Depth Features of Stacked Autoencoders and Original Variables for Oil Dry Point Soft Sensor","publication_year":2018,"publication_date":"2018-12-14","ids":{"openalex":"https://openalex.org/W2904750179","doi":"https://doi.org/10.1109/access.2018.2886820","mag":"2904750179"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2886820","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2886820","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08576528.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":null,"license_id":null,"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/ielx7/6287639/8600701/08576528.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101891532","display_name":"Jie Wang","orcid":"https://orcid.org/0000-0001-8846-398X"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Wang","raw_affiliation_strings":["Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000809799","display_name":"Xuefeng Yan","orcid":"https://orcid.org/0000-0001-5622-8686"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Yan","raw_affiliation_strings":["Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101891532"],"corresponding_institution_ids":["https://openalex.org/I143593769"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.3094,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82222296,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"1981","last_page":"1990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9993000030517578,"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":0.9993000030517578,"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/T10320","display_name":"Neural Networks and Applications","score":0.9861999750137329,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9805999994277954,"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/soft-sensor","display_name":"Soft sensor","score":0.7148508429527283},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6589567065238953},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.6252555251121521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5558727383613586},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5442233085632324},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5337558388710022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4974963963031769},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4947302043437958},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.48790213465690613},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46187806129455566},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.45913511514663696},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.43739259243011475},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3992263972759247},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3607766628265381},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.23551425337791443},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2039451003074646}],"concepts":[{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.7148508429527283},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6589567065238953},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.6252555251121521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5558727383613586},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5442233085632324},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5337558388710022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4974963963031769},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4947302043437958},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.48790213465690613},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46187806129455566},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.45913511514663696},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.43739259243011475},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3992263972759247},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3607766628265381},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.23551425337791443},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2039451003074646},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2886820","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2886820","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08576528.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f4735f87f40f4ec89f62275e2122fc0c","is_oa":true,"landing_page_url":"https://doaj.org/article/f4735f87f40f4ec89f62275e2122fc0c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"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 7, Pp 1981-1990 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2886820","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2886820","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08576528.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":null,"license_id":null,"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/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2376276132","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3120317670","display_name":null,"funder_award_id":"2187808","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5986248920","display_name":null,"funder_award_id":"2222017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6090383080","display_name":null,"funder_award_id":"222201717006","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6905653140","display_name":null,"funder_award_id":"21878081","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7322391923","display_name":null,"funder_award_id":"222201717006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8951484681","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904750179.pdf","grobid_xml":"https://content.openalex.org/works/W2904750179.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1991797370","https://openalex.org/W2001803682","https://openalex.org/W2029469881","https://openalex.org/W2085862958","https://openalex.org/W2116141292","https://openalex.org/W2134465446","https://openalex.org/W2154053567","https://openalex.org/W2164122462","https://openalex.org/W2321627895","https://openalex.org/W2460943568","https://openalex.org/W2522553089","https://openalex.org/W2534400386","https://openalex.org/W2539756354","https://openalex.org/W2548389064","https://openalex.org/W2580977989","https://openalex.org/W2583812186","https://openalex.org/W2625354259","https://openalex.org/W2742763523","https://openalex.org/W2779012937","https://openalex.org/W2789440825","https://openalex.org/W2794234348","https://openalex.org/W2919115771","https://openalex.org/W4242361954"],"related_works":["https://openalex.org/W2374290272","https://openalex.org/W2504004674","https://openalex.org/W2097933059","https://openalex.org/W2466816617","https://openalex.org/W4386158748","https://openalex.org/W1987679298","https://openalex.org/W2963177394","https://openalex.org/W4313359513","https://openalex.org/W2498744856","https://openalex.org/W4390482104"],"abstract_inverted_index":{"In":[0],"modern":[1],"chemical":[2],"process":[3],"control,":[4],"the":[5,48,71,74,85,94,107,113,124,134,138,158,169,188,202],"application":[6],"of":[7,50,73,129,172,187],"data-driven":[8],"soft":[9,22,170],"sensor":[10,171],"has":[11],"become":[12],"increasingly":[13],"extensive.":[14],"Feature":[15],"extraction":[16,27],"is":[17],"an":[18,64,82],"important":[19],"step":[20],"in":[21,59,185,201],"sensor.":[23],"A":[24],"novel":[25],"feature":[26],"and":[28,36,56,88,109,112,127,165,193,204,209],"integration":[29],"method":[30,115],"based":[31],"on":[32,52,93],"stacked":[33],"autoencoders":[34],"(SAE)":[35],"mutual":[37],"information":[38,51],"(MI)-weighted":[39],"principle":[40,135,139],"component":[41],"analysis":[42],"(PCA)":[43],"was":[44,67,100,116,154,205],"proposed":[45,180],"to":[46,69,102,106,118,132,143,168],"solve":[47],"loss":[49],"shallow":[53],"depth":[54],"features":[55,72,89,108,128],"original":[57,75,86,110,125],"variables":[58,76,87,126],"neural":[60,150],"network":[61],"models.":[62],"First,":[63],"SAE":[65],"model":[66,153,181],"trained":[68],"extract":[70],"with":[77,90],"varying":[78,130],"depths.":[79],"Second,":[80],"through":[81],"MI":[83,99],"indicator,":[84],"strong":[91],"dependency":[92],"outputs":[95],"were":[96,141],"selected.":[97],"Then,":[98],"used":[101,117,142],"assign":[103],"varied":[104],"weights":[105],"variables,":[111],"PCA":[114],"remove":[119],"any":[120],"possible":[121],"redundancy":[122],"between":[123],"depths":[131],"obtain":[133],"components.":[136],"Finally,":[137],"components":[140],"construct":[144],"a":[145,149,163,173],"regressor,":[146],"such":[147],"as":[148,162],"network.":[151],"The":[152,179],"first":[155],"tested":[156],"using":[157],"Boston":[159],"housing":[160],"dataset":[161],"benchmark":[164],"then":[166],"applied":[167],"constant":[174],"top":[175],"oil":[176],"dry":[177],"point.":[178],"achieved":[182],"optimal":[183],"results":[184],"terms":[186],"root":[189],"mean":[190],"squared":[191],"error":[192],"<inline-formula":[194],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[195],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[196],"<tex-math":[197],"notation=\"LaTeX\">$r$":[198],"</tex-math></inline-formula>":[199],"indicators":[200],"experiments":[203],"thus":[206],"proved":[207],"feasible":[208],"useful.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}