{"id":"https://openalex.org/W4415593626","doi":"https://doi.org/10.1109/tase.2025.3625751","title":"Multiobjective Semi-Supervised Ensemble Learning and Its Application in Iron and Steel Industry","display_name":"Multiobjective Semi-Supervised Ensemble Learning and Its Application in Iron and Steel Industry","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415593626","doi":"https://doi.org/10.1109/tase.2025.3625751"},"language":null,"primary_location":{"id":"doi:10.1109/tase.2025.3625751","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2025.3625751","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Automation Science and Engineering","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":null,"display_name":"Yao Wang","orcid":"https://orcid.org/0009-0002-5614-8656"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yao Wang","raw_affiliation_strings":["School of Software, Nanjing University of Information Science and Technology, Nanjing, China","School of Software, Nanjing University of Information Science & Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]},{"raw_affiliation_string":"School of Software, Nanjing University of Information Science & Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080165465","display_name":"Xianpeng Wang","orcid":"https://orcid.org/0000-0001-8132-9446"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianpeng Wang","raw_affiliation_strings":["National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101843709","display_name":"Xue Yu","orcid":"https://orcid.org/0000-0002-0726-3407"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Xue","raw_affiliation_strings":["School of Software, Nanjing University of Information Science and Technology, Nanjing, China","School of Software, Nanjing University of Information Science & Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]},{"raw_affiliation_string":"School of Software, Nanjing University of Information Science & Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":null,"apc_paid":null,"fwci":1.3591,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.82389415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"22","issue":null,"first_page":"23051","last_page":"23065"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.4375999867916107,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12282","display_name":"Mineral Processing and Grinding","score":0.4375999867916107,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T14474","display_name":"Industrial Technology and Control Systems","score":0.43619999289512634,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.42480000853538513,"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/ensemble-learning","display_name":"Ensemble learning","score":0.7232000231742859},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5522000193595886},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5166000127792358},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5037000179290771},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.5030999779701233},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.4961000084877014},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.49239999055862427},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4311999976634979},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.41370001435279846},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3815999925136566}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.7232000231742859},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6851000189781189},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6678000092506409},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6444000005722046},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5522000193595886},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5166000127792358},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5037000179290771},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.5030999779701233},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.4961000084877014},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.49239999055862427},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3815999925136566},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33329999446868896},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.32670000195503235},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.2736000120639801},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C135510737","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance indicator","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2025.3625751","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2025.3625751","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2383022881","display_name":null,"funder_award_id":"61876089","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2502571905","display_name":null,"funder_award_id":"62376127","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5403677301","display_name":null,"funder_award_id":"62473086","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6085332701","display_name":null,"funder_award_id":"1513142501049","funder_id":"https://openalex.org/F4320335990","funder_display_name":"Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335990","display_name":"Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1525375343","https://openalex.org/W1677182931","https://openalex.org/W2074616700","https://openalex.org/W2101807845","https://openalex.org/W2126105956","https://openalex.org/W2133176659","https://openalex.org/W2143381319","https://openalex.org/W2295598076","https://openalex.org/W2471161958","https://openalex.org/W2591797778","https://openalex.org/W2736299552","https://openalex.org/W2742763523","https://openalex.org/W2799747280","https://openalex.org/W2887063112","https://openalex.org/W2887065738","https://openalex.org/W2890644749","https://openalex.org/W2895084243","https://openalex.org/W2940678998","https://openalex.org/W2963946985","https://openalex.org/W2976026359","https://openalex.org/W2984353870","https://openalex.org/W3001458159","https://openalex.org/W3006987371","https://openalex.org/W3034190797","https://openalex.org/W3088798822","https://openalex.org/W3091563199","https://openalex.org/W3134254543","https://openalex.org/W3165140781","https://openalex.org/W3167548703","https://openalex.org/W3187004996","https://openalex.org/W3192682950","https://openalex.org/W3205631417","https://openalex.org/W3214102707","https://openalex.org/W4214660441","https://openalex.org/W4310208881","https://openalex.org/W4318595446","https://openalex.org/W4321019697","https://openalex.org/W4321195933","https://openalex.org/W4382372076","https://openalex.org/W4382998509","https://openalex.org/W4385237430","https://openalex.org/W4386896116","https://openalex.org/W4389104760","https://openalex.org/W4390322892","https://openalex.org/W4390561780","https://openalex.org/W4391643855","https://openalex.org/W4394578698","https://openalex.org/W4405890499","https://openalex.org/W4406237488"],"related_works":[],"abstract_inverted_index":{"High-quality":[0],"predictions":[1],"of":[2,37,59,111,136,161,176,183,247,251,260],"key":[3,211],"indicators":[4],"are":[5,191],"essential":[6],"to":[7,47,63,127,149,201,231],"maintain":[8],"stable":[9],"production":[10,45],"in":[11,43,66,88,215],"the":[12,34,49,55,99,104,115,152,168,173,177,203,216,239,245,258],"iron":[13,217],"and":[14,57,108,118,134,158,189,193,218,236],"steel":[15,219],"industry.":[16],"However,":[17],"most":[18],"existing":[19,240],"prediction":[20,213],"methods":[21,30,61],"rely":[22],"on":[23,209,253],"manually":[24],"designed":[25],"supervised":[26,159],"learning":[27,80,153,157,174,234,242],"models.":[28],"These":[29],"do":[31],"not":[32],"consider":[33],"effective":[35],"utilization":[36],"unlabeled":[38,165],"data,":[39],"which":[40,89],"is":[41,96,125,147],"prevalent":[42],"practical":[44],"environments,":[46],"improve":[48],"model":[50],"performance.":[51],"As":[52],"a":[53,76,90,181,196,248,254],"result,":[54],"accuracy":[56,133,229],"generalization":[58],"these":[60],"tend":[62],"perform":[64],"poorly":[65],"real-world":[67],"applications.":[68],"To":[69],"tackle":[70],"this":[71,73],"issue,":[72],"paper":[74],"develops":[75],"multiobjective":[77],"semi-supervised":[78,156],"ensemble":[79,199,205],"method":[81,200],"with":[82,187],"evolutionary":[83],"neural":[84,93,109],"architecture":[85,110],"search":[86],"(MOSSEL-ENAS),":[87],"one-dimensional":[91],"convolutional":[92],"network":[94],"(OD-CNN)":[95],"employed":[97],"as":[98,114],"base":[100,138,185],"learner.":[101,139],"MOSSEL-ENAS":[102,223,252],"takes":[103],"input":[105],"feature":[106],"permutation":[107],"each":[112,137],"OD-CNN":[113],"decision":[116],"variables,":[117],"an":[119,141],"improved":[120],"non-dominated":[121],"sorting":[122],"genetic":[123],"algorithm":[124],"developed":[126],"simultaneously":[128],"optimize":[129],"two":[130,210],"objectives,":[131],"i.e.,":[132],"complexity":[135],"Moreover,":[140],"adaptive":[142],"evaluation":[143],"pattern":[144],"adjustment":[145],"strategy":[146],"proposed":[148],"adaptively":[150],"adjust":[151],"paradigm":[154],"(i.e.,":[155],"learning)":[160],"OD-CNNs":[162],"by":[163],"incorporating":[164],"data":[166],"into":[167],"training":[169],"process,":[170],"further":[171],"improving":[172],"performance":[175],"algorithm.":[178],"After":[179],"evolution,":[180],"set":[182],"elite":[184],"learners":[186],"high-accuracy":[188],"low-complexity":[190],"selected":[192],"combined":[194],"using":[195],"LightGBM-based":[197],"stacking":[198],"construct":[202],"final":[204],"model.":[206],"Experimental":[207],"results":[208],"indicator":[212],"tasks":[214],"industry":[220],"demonstrate":[221],"that":[222],"achieves":[224],"competitive":[225],"or":[226],"even":[227],"better":[228],"compared":[230],"other":[232],"powerful":[233],"methods,":[235],"also":[237],"outperforms":[238],"task-specific":[241],"methods.":[243],"Furthermore,":[244],"competitiveness":[246],"modified":[249],"version":[250],"classification":[255],"task":[256],"highlights":[257],"scalability":[259],"our":[261],"proposal.":[262]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-28T00:00:00"}