{"id":"https://openalex.org/W3182574379","doi":"https://doi.org/10.1109/tii.2021.3096840","title":"Hybrid Parallel Stochastic Configuration Networks for Industrial Data Analytics","display_name":"Hybrid Parallel Stochastic Configuration Networks for Industrial Data Analytics","publication_year":2021,"publication_date":"2021-07-30","ids":{"openalex":"https://openalex.org/W3182574379","doi":"https://doi.org/10.1109/tii.2021.3096840","mag":"3182574379"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2021.3096840","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2021.3096840","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","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":"https://openalex.org/A5085295698","display_name":"Wei Dai","orcid":"https://orcid.org/0000-0003-3057-7225"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]},{"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":"Wei Dai","raw_affiliation_strings":["Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining Technology, Xuzhou, China","State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0003-3057-7225","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025993851","display_name":"Xinyu Zhou","orcid":"https://orcid.org/0000-0001-9443-5256"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Zhou","raw_affiliation_strings":["Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048129965","display_name":"Depeng Li","orcid":"https://orcid.org/0000-0002-2281-7535"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Depeng Li","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013161489","display_name":"Song Zhu","orcid":"https://orcid.org/0000-0001-5228-9406"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Zhu","raw_affiliation_strings":["School of Mathematics, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108064895","display_name":"Xuesong Wang","orcid":"https://orcid.org/0000-0002-5327-1088"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Wang","raw_affiliation_strings":["Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5327-1088","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.9201,"has_fulltext":false,"cited_by_count":118,"citation_normalized_percentile":{"value":0.98675062,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"18","issue":"4","first_page":"2331","last_page":"2341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"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":0.9998999834060669,"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/T10320","display_name":"Neural Networks and Applications","score":0.9970999956130981,"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/T10057","display_name":"Face and Expression Recognition","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7807495594024658},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6735507249832153},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5949550867080688},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5515718460083008},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5200207233428955},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4765634834766388},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4378197491168976},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.42415645718574524},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4013046622276306},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37800222635269165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3296108841896057},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10994863510131836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7807495594024658},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6735507249832153},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5949550867080688},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5515718460083008},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5200207233428955},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4765634834766388},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4378197491168976},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.42415645718574524},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4013046622276306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37800222635269165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3296108841896057},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10994863510131836},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2021.3096840","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2021.3096840","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G2910164624","display_name":null,"funder_award_id":"2018T110571","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G3776651585","display_name":null,"funder_award_id":"61973306","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6946442576","display_name":null,"funder_award_id":"BK20200086","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1551112541","https://openalex.org/W1981972832","https://openalex.org/W1986278072","https://openalex.org/W2012638612","https://openalex.org/W2040825652","https://openalex.org/W2059617729","https://openalex.org/W2074464748","https://openalex.org/W2089671642","https://openalex.org/W2586160710","https://openalex.org/W2593382986","https://openalex.org/W2728075319","https://openalex.org/W2790226641","https://openalex.org/W2795943779","https://openalex.org/W2913497545","https://openalex.org/W2915771068","https://openalex.org/W2917680112","https://openalex.org/W2921936057","https://openalex.org/W2942877765","https://openalex.org/W2948014336","https://openalex.org/W2991207885","https://openalex.org/W2992572750","https://openalex.org/W3006156969","https://openalex.org/W3006625545","https://openalex.org/W3016077482","https://openalex.org/W3037551640","https://openalex.org/W3045307933","https://openalex.org/W3119363261","https://openalex.org/W3128495154"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W4318719684","https://openalex.org/W4389724018","https://openalex.org/W4318559728","https://openalex.org/W3183136280","https://openalex.org/W2775233965","https://openalex.org/W3114716045","https://openalex.org/W4360995913"],"abstract_inverted_index":{"As":[0],"a":[1,16,46,77,84,88,96,157,165],"class":[2],"of":[3,71,104,179],"randomized":[4],"learner":[5],"model,":[6],"stochastic":[7],"configuration":[8],"networks":[9],"(SCNs)":[10],"have":[11],"been":[12],"successfully":[13],"applied":[14],"in":[15,124],"few":[17],"data":[18,25,89],"analytics":[19],"tasks.":[20],"Given":[21],"the":[22,29,56,69,102,122,125,134,149,153,177,180],"industrial":[23,159],"big":[24],"modeling":[26],"tasks,":[27],"however,":[28],"original":[30],"SCNs":[31,44,53,62],"potentially":[32],"lead":[33],"to":[34,45,100,128],"excessive":[35],"training":[36],"time.":[37],"To":[38],"this":[39,41,112],"end,":[40],"article":[42,113],"extends":[43],"hybrid":[47,51,57],"parallel":[48,52,58,90],"version,":[49],"termed":[50],"(HPSCNs).":[54],"In":[55],"learning":[59,135],"algorithm,":[60,79],"two":[61,70],"are":[63,139],"synchronously":[64],"constructed.":[65],"The":[66],"difference":[67],"between":[68],"them":[72],"is":[73,92,162,171],"that":[74],"one":[75,82],"employs":[76],"point-incremental":[78],"and":[80],"another":[81],"adopts":[83],"block-incremental":[85],"algorithm.":[86,182],"Moreover,":[87],"method":[91],"established":[93],"based":[94,173],"on":[95,152,174],"dynamic":[97],"block":[98],"strategy":[99],"accelerate":[101],"establishment":[103],"candidate":[105],"node":[106],"pool":[107],"for":[108],"each":[109],"SCN.":[110],"Additionally,":[111],"proposes":[114],"an":[115],"adaptive":[116],"hyperparameter":[117],"adjustment":[118],"method,":[119],"which":[120],"allows":[121],"hyperparameters":[123],"supervisory":[126],"mechanism":[127],"be":[129],"automatically":[130],"adjusted":[131],"along":[132],"with":[133],"process.":[136],"Comparative":[137],"experiments":[138],"first":[140],"conducted":[141],"through":[142],"four":[143],"large-scale":[144],"benchmark":[145],"datasets,":[146],"followed":[147],"by":[148],"fully":[150],"discussion":[151],"algorithm":[154],"parameters.":[155],"Finally,":[156],"practical":[158],"application":[160],"case":[161],"made,":[163],"where":[164],"grinding":[166],"particle":[167],"size":[168],"soft":[169],"sensor":[170],"developed":[172],"HPSCN,":[175],"showing":[176],"effectiveness":[178],"proposed":[181]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":61},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":8}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}