{"id":"https://openalex.org/W4313182445","doi":"https://doi.org/10.1109/tim.2022.3219475","title":"Temporal Hypergraph Attention Network for Silicon Content Prediction in Blast Furnace","display_name":"Temporal Hypergraph Attention Network for Silicon Content Prediction in Blast Furnace","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4313182445","doi":"https://doi.org/10.1109/tim.2022.3219475"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3219475","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3219475","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5038674178","display_name":"Chengbao Liu","orcid":"https://orcid.org/0000-0003-2078-9101"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengbao Liu","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2078-9101","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037083362","display_name":"Jie Tan","orcid":"https://orcid.org/0000-0003-3603-6147"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tan","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3603-6147","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416946","display_name":"Jingwei Li","orcid":"https://orcid.org/0000-0003-0143-7338"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwei Li","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0143-7338","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101841379","display_name":"Yuan Li","orcid":"https://orcid.org/0000-0001-9022-7345"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Li","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9022-7345","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076196391","display_name":"Huanjie Wang","orcid":"https://orcid.org/0000-0002-7817-3804"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanjie Wang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7817-3804","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7773,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.65289955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11837","display_name":"Iron and Steelmaking Processes","score":0.9904999732971191,"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/T11837","display_name":"Iron and Steelmaking Processes","score":0.9904999732971191,"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/T14392","display_name":"Geoscience and Mining Technology","score":0.9506000280380249,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.948199987411499,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/blast-furnace","display_name":"Blast furnace","score":0.8220838308334351},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6412431001663208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5658407211303711},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.561120867729187},{"id":"https://openalex.org/keywords/silicon","display_name":"Silicon","score":0.5300809144973755},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5188659429550171},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.5151475667953491},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4382016956806183},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3592941164970398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3563241958618164},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19106590747833252},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1872374713420868},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15164265036582947},{"id":"https://openalex.org/keywords/metallurgy","display_name":"Metallurgy","score":0.08078426122665405}],"concepts":[{"id":"https://openalex.org/C2780269488","wikidata":"https://www.wikidata.org/wiki/Q181485","display_name":"Blast furnace","level":2,"score":0.8220838308334351},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6412431001663208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5658407211303711},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.561120867729187},{"id":"https://openalex.org/C544956773","wikidata":"https://www.wikidata.org/wiki/Q670","display_name":"Silicon","level":2,"score":0.5300809144973755},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5188659429550171},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.5151475667953491},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4382016956806183},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3592941164970398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3563241958618164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19106590747833252},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1872374713420868},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15164265036582947},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.08078426122665405},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3219475","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3219475","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G771824490","display_name":null,"funder_award_id":"62003344","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8060992238","display_name":null,"funder_award_id":"2020YFB1711101","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W747162797","https://openalex.org/W1974514382","https://openalex.org/W1987597436","https://openalex.org/W1996179078","https://openalex.org/W2029246249","https://openalex.org/W2137611688","https://openalex.org/W2145313009","https://openalex.org/W2165700458","https://openalex.org/W2186941161","https://openalex.org/W2389595022","https://openalex.org/W2616764804","https://openalex.org/W2739799890","https://openalex.org/W2757342969","https://openalex.org/W2767358759","https://openalex.org/W2770837308","https://openalex.org/W2892880750","https://openalex.org/W2901504064","https://openalex.org/W2907492528","https://openalex.org/W2948334075","https://openalex.org/W3002196107","https://openalex.org/W3014899889","https://openalex.org/W3015673973","https://openalex.org/W3080838336","https://openalex.org/W3085990079","https://openalex.org/W3088707884","https://openalex.org/W3093989243","https://openalex.org/W3097572646","https://openalex.org/W3102020143","https://openalex.org/W3104355095","https://openalex.org/W3106229813","https://openalex.org/W3123909522","https://openalex.org/W3134254543","https://openalex.org/W3143559563","https://openalex.org/W3152893301","https://openalex.org/W3187582009","https://openalex.org/W3199132820","https://openalex.org/W4297733535","https://openalex.org/W4327652946","https://openalex.org/W6786266798","https://openalex.org/W6838691670"],"related_works":["https://openalex.org/W4376608589","https://openalex.org/W3138003926","https://openalex.org/W4300037846","https://openalex.org/W1630514295","https://openalex.org/W1537073411","https://openalex.org/W2963081352","https://openalex.org/W2472555608","https://openalex.org/W4376608938","https://openalex.org/W4288275998","https://openalex.org/W4214498971"],"abstract_inverted_index":{"Online":[0],"dynamic":[1],"prediction":[2,47,62],"of":[3,95,107,121,131,151],"the":[4,10,19,24,31,54,73,79,86,92,105,111,118,127,135,152],"hot":[5],"metal":[6],"silicon":[7,40,45,60],"content":[8,41,46,61],"in":[9,169],"blast":[11,160,167],"furnace":[12,20,161,168],"ironmaking":[13,162],"process":[14,43,132,163],"is":[15,48,71,88,114,156],"crucial":[16],"for":[17],"stabilizing":[18],"condition":[21],"and":[22,35,42,78,98,110,142],"improving":[23],"molten":[25],"iron":[26],"quality.":[27],"However,":[28],"due":[29],"to":[30,90,103,116,125],"complex":[32,146],"nonlinear":[33],"correlations":[34,94,141],"time-varying":[36,128],"time":[37,129],"lags":[38,130],"between":[39],"variables,":[44],"a":[49,58,166],"challenging":[50],"task.":[51],"To":[52],"tackle":[53],"problem,":[55],"we":[56],"propose":[57],"novel":[59],"method,":[63],"called":[64],"temporal":[65],"hypergraph":[66,74],"attention":[67,75],"network":[68,76,113],"(T-HyperGAT),":[69],"which":[70],"combined":[72],"(HyperGAT)":[77],"gated":[80],"recurrent":[81],"unit":[82],"(GRU)":[83],"network.":[84],"Specifically,":[85],"Hyper-GAT":[87],"used":[89,115],"capture":[91,117,139],"high-order":[93,140],"input":[96,108,123],"features":[97,124],"perform":[99],"equal-dimensional":[100],"feature":[101],"transformation":[102],"maintain":[104],"temporality":[106],"features,":[109],"GRU":[112],"time-series":[119,143],"characteristics":[120,144],"transformed":[122],"overcome":[126],"variables.":[133],"Then":[134],"T-HyperGAT":[136,154],"model":[137],"can":[138],"from":[145,165],"industrial":[147],"data.":[148],"The":[149],"effectiveness":[150],"proposed":[153],"method":[155],"verified":[157],"by":[158],"actual":[159],"data":[164],"China.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
