{"id":"https://openalex.org/W3155377928","doi":"https://doi.org/10.1007/s00521-021-05984-x","title":"A Deep Learning-based approach for forecasting off-gas production and consumption in the blast furnace","display_name":"A Deep Learning-based approach for forecasting off-gas production and consumption in the blast furnace","publication_year":2021,"publication_date":"2021-04-16","ids":{"openalex":"https://openalex.org/W3155377928","doi":"https://doi.org/10.1007/s00521-021-05984-x","mag":"3155377928","pmid":"https://pubmed.ncbi.nlm.nih.gov/33879977"},"language":"en","primary_location":{"id":"doi:10.1007/s00521-021-05984-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-05984-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-021-05984-x.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00521-021-05984-x.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057674100","display_name":"Stefano Dettori","orcid":"https://orcid.org/0000-0003-4336-0770"},"institutions":[{"id":"https://openalex.org/I162290304","display_name":"Scuola Superiore Sant'Anna","ror":"https://ror.org/025602r80","country_code":"IT","type":"education","lineage":["https://openalex.org/I162290304"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Stefano Dettori","raw_affiliation_strings":["Scuola Superiore Sant'Anna - TeCIP Institute - ICT-COISP, Pisa, Italy","Scuola Superiore Sant'Anna \u00ad TeCIP Institute \u2013 ICT-COISP, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0003-4336-0770","affiliations":[{"raw_affiliation_string":"Scuola Superiore Sant'Anna - TeCIP Institute - ICT-COISP, Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]},{"raw_affiliation_string":"Scuola Superiore Sant'Anna \u00ad TeCIP Institute \u2013 ICT-COISP, Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007790196","display_name":"Ismael Matino","orcid":"https://orcid.org/0000-0002-9633-5491"},"institutions":[{"id":"https://openalex.org/I162290304","display_name":"Scuola Superiore Sant'Anna","ror":"https://ror.org/025602r80","country_code":"IT","type":"education","lineage":["https://openalex.org/I162290304"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Ismael Matino","raw_affiliation_strings":["Scuola Superiore Sant'Anna - TeCIP Institute - ICT-COISP, Pisa, Italy","Scuola Superiore Sant'Anna \u00ad TeCIP Institute \u2013 ICT-COISP, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0002-9633-5491","affiliations":[{"raw_affiliation_string":"Scuola Superiore Sant'Anna - TeCIP Institute - ICT-COISP, Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]},{"raw_affiliation_string":"Scuola Superiore Sant'Anna \u00ad TeCIP Institute \u2013 ICT-COISP, Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033400760","display_name":"Valentina Colla","orcid":"https://orcid.org/0000-0002-9574-0575"},"institutions":[{"id":"https://openalex.org/I162290304","display_name":"Scuola Superiore Sant'Anna","ror":"https://ror.org/025602r80","country_code":"IT","type":"education","lineage":["https://openalex.org/I162290304"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Valentina Colla","raw_affiliation_strings":["Scuola Superiore Sant'Anna - TeCIP Institute - ICT-COISP, Pisa, Italy","Scuola Superiore Sant'Anna \u00ad TeCIP Institute \u2013 ICT-COISP, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0002-9574-0575","affiliations":[{"raw_affiliation_string":"Scuola Superiore Sant'Anna - TeCIP Institute - ICT-COISP, Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]},{"raw_affiliation_string":"Scuola Superiore Sant'Anna \u00ad TeCIP Institute \u2013 ICT-COISP, Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007209223","display_name":"Ramon Speets","orcid":null},"institutions":[{"id":"https://openalex.org/I27485261","display_name":"Tata Steel (Netherlands)","ror":"https://ror.org/00925cq50","country_code":"NL","type":"company","lineage":["https://openalex.org/I27485261","https://openalex.org/I4210086519","https://openalex.org/I87816474"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ramon Speets","raw_affiliation_strings":["Tata Steel, CA IJmuiden, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tata Steel, CA IJmuiden, The Netherlands","institution_ids":["https://openalex.org/I27485261"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057674100"],"corresponding_institution_ids":["https://openalex.org/I162290304"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":3.5191,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.93641756,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"34","issue":"2","first_page":"911","last_page":"923"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.4528000056743622,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.4528000056743622,"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/T11837","display_name":"Iron and Steelmaking Processes","score":0.09080000221729279,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.05530000105500221,"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/computational-science-and-engineering","display_name":"Computational Science and Engineering","score":0.824069082736969},{"id":"https://openalex.org/keywords/blast-furnace","display_name":"Blast furnace","score":0.6710786819458008},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.6180906891822815},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5456233620643616},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.5357164144515991},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46450966596603394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4310641884803772},{"id":"https://openalex.org/keywords/gas-consumption","display_name":"Gas consumption","score":0.41473981738090515},{"id":"https://openalex.org/keywords/process-engineering","display_name":"Process engineering","score":0.39687395095825195},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3786845803260803},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3786022365093231},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.19974330067634583},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12788331508636475},{"id":"https://openalex.org/keywords/metallurgy","display_name":"Metallurgy","score":0.12025311589241028},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.08941838145256042}],"concepts":[{"id":"https://openalex.org/C68597687","wikidata":"https://www.wikidata.org/wiki/Q362601","display_name":"Computational Science and Engineering","level":2,"score":0.824069082736969},{"id":"https://openalex.org/C2780269488","wikidata":"https://www.wikidata.org/wiki/Q181485","display_name":"Blast furnace","level":2,"score":0.6710786819458008},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.6180906891822815},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5456233620643616},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.5357164144515991},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46450966596603394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4310641884803772},{"id":"https://openalex.org/C2992367939","wikidata":"https://www.wikidata.org/wiki/Q4121144","display_name":"Gas consumption","level":2,"score":0.41473981738090515},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.39687395095825195},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3786845803260803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3786022365093231},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.19974330067634583},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12788331508636475},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.12025311589241028},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.08941838145256042},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s00521-021-05984-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-05984-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-021-05984-x.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},{"id":"pmid:33879977","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33879977","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural computing & applications","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8051551","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8051551","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Neural Comput Appl","raw_type":"Text"},{"id":"pmh:oai:www.iris.sssup.it:11382/538346","is_oa":false,"landing_page_url":"http://hdl.handle.net/11382/538346","pdf_url":null,"source":{"id":"https://openalex.org/S4377196376","display_name":"CINECA IRIS Institutional Research Information System (Sant'Anna School of Advanced Studies)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I162290304","host_organization_name":"Scuola Superiore Sant'Anna","host_organization_lineage":["https://openalex.org/I162290304"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s00521-021-05984-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-05984-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-021-05984-x.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G608501366","display_name":null,"funder_award_id":"RFSR-CT-2015-00029","funder_id":"https://openalex.org/F4320335997","funder_display_name":"Research Fund for Coal and Steel"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320324216","display_name":"Scuola Superiore Sant'Anna","ror":"https://ror.org/025602r80"},{"id":"https://openalex.org/F4320335997","display_name":"Research Fund for Coal and Steel","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3155377928.pdf","grobid_xml":"https://content.openalex.org/works/W3155377928.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W146276783","https://openalex.org/W1522301498","https://openalex.org/W1652242680","https://openalex.org/W1729113910","https://openalex.org/W1815076433","https://openalex.org/W1908962573","https://openalex.org/W1986843940","https://openalex.org/W1989312953","https://openalex.org/W2011153518","https://openalex.org/W2033323453","https://openalex.org/W2036609814","https://openalex.org/W2058804598","https://openalex.org/W2061225002","https://openalex.org/W2062803420","https://openalex.org/W2064675550","https://openalex.org/W2096614992","https://openalex.org/W2097998348","https://openalex.org/W2103179919","https://openalex.org/W2103452139","https://openalex.org/W2106437164","https://openalex.org/W2107878631","https://openalex.org/W2166107799","https://openalex.org/W2552913538","https://openalex.org/W2604037920","https://openalex.org/W2608997467","https://openalex.org/W2611445505","https://openalex.org/W2767568774","https://openalex.org/W2802465900","https://openalex.org/W2885420314","https://openalex.org/W2921905922","https://openalex.org/W2946558031","https://openalex.org/W2963003308","https://openalex.org/W2965777924","https://openalex.org/W3007452371","https://openalex.org/W3022431777","https://openalex.org/W3041416709","https://openalex.org/W3080272186","https://openalex.org/W3121448636","https://openalex.org/W6631190155"],"related_works":["https://openalex.org/W2377653417","https://openalex.org/W2384018951","https://openalex.org/W2334153802","https://openalex.org/W2391355765","https://openalex.org/W2609592912","https://openalex.org/W2076166075","https://openalex.org/W2356730094","https://openalex.org/W2390382820","https://openalex.org/W2393821008","https://openalex.org/W2036609814"],"abstract_inverted_index":{"This":[0],"article":[1,33],"presents":[2],"the":[3,13,19,29,35,44,50,58,87,93,97,133],"application":[4],"of":[5,23,28,43,62,75,95,105,130,135,154],"a":[6,39,63,73],"recent":[7],"neural":[8,77],"network":[9,17],"topology":[10],"known":[11],"as":[12,72],"deep":[14,136],"echo":[15,137],"state":[16,138],"to":[18,56,68,147],"prediction":[20],"and":[21,47,60,101,108,117,119,140,157],"modeling":[22],"strongly":[24],"nonlinear":[25],"systems":[26],"typical":[27],"process":[30],"industry.":[31],"The":[32,103,128,161],"analyzes":[34],"results":[36,131],"by":[37],"introducing":[38],"comparison":[40],"with":[41,92,145],"one":[42,69],"most":[45],"common":[46,85],"efficient":[48],"topologies,":[49],"long":[51],"short-term":[52],"memories,":[53],"in":[54,86,152],"order":[55],"highlight":[57],"strengths":[59],"weaknesses":[61],"reservoir":[64],"computing":[65],"approach":[66],"compared":[67],"currently":[70],"considered":[71],"standard":[74,148],"recurrent":[76,149],"network.":[78],"As":[79],"benchmark":[80],"application,":[81],"two":[82],"specific":[83],"processes":[84],"integrated":[88],"steelworks":[89],"are":[90,110],"selected,":[91],"purpose":[94],"forecasting":[96,143],"future":[98],"energy":[99],"exchanges":[100],"transformations.":[102],"procedures":[104,156],"training,":[106],"validation":[107],"test":[109],"based":[111],"on":[112],"data":[113],"analysis,":[114],"outlier":[115],"detection":[116],"reconciliation":[118],"variable":[120],"selection":[121],"starting":[122],"from":[123],"real":[124],"field":[125],"industrial":[126],"data.":[127],"analysis":[129],"shows":[132],"effectiveness":[134],"networks":[139],"their":[141],"strong":[142],"capabilities":[144],"respect":[146],"methodologies":[150],"both":[151],"terms":[153],"training":[155],"accuracy.":[158],"Supplementary":[159],"Information:":[160],"online":[162],"version":[163],"contains":[164],"supplementary":[165],"material":[166],"available":[167],"at":[168],"10.1007/s00521-021-05984-x.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}