{"id":"https://openalex.org/W2782686425","doi":"https://doi.org/10.1109/etfa.2017.8247618","title":"Surrogate models for design and study of underground mine ventilation","display_name":"Surrogate models for design and study of underground mine ventilation","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2782686425","doi":"https://doi.org/10.1109/etfa.2017.8247618","mag":"2782686425"},"language":"en","primary_location":{"id":"doi:10.1109/etfa.2017.8247618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2017.8247618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298572","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000509708","display_name":"Max \u00c5strand","orcid":null},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Max Astrand","raw_affiliation_strings":["ABB Corporate Research & KTH, Royal Institute of Technology, V\u00e4ster\u00e5s / Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"ABB Corporate Research & KTH, Royal Institute of Technology, V\u00e4ster\u00e5s / Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112342049","display_name":"Kari Saarinen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210086503","display_name":"ABB (Sweden)","ror":"https://ror.org/0033n4009","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210086503","https://openalex.org/I885143765"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Kari Saarinen","raw_affiliation_strings":["ABB Corporate Research, V\u00e4ster\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"ABB Corporate Research, V\u00e4ster\u00e5s, Sweden","institution_ids":["https://openalex.org/I4210086503"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003308056","display_name":"Shiva Sander-Tavallaey","orcid":"https://orcid.org/0000-0001-6551-9784"},"institutions":[{"id":"https://openalex.org/I4210086503","display_name":"ABB (Sweden)","ror":"https://ror.org/0033n4009","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210086503","https://openalex.org/I885143765"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Shiva Sander-Tavallaey","raw_affiliation_strings":["ABB Corporate Research, V\u00e4ster\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"ABB Corporate Research, V\u00e4ster\u00e5s, Sweden","institution_ids":["https://openalex.org/I4210086503"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000509708"],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.19957983,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9969000220298767,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/surrogate-model","display_name":"Surrogate model","score":0.8714789152145386},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7082496285438538},{"id":"https://openalex.org/keywords/matlab","display_name":"MATLAB","score":0.6377630233764648},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6107237339019775},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5372633337974548},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4766336679458618},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.45921066403388977},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.4520159363746643},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3932020664215088},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3480601906776428},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.2750568985939026},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22405248880386353}],"concepts":[{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.8714789152145386},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7082496285438538},{"id":"https://openalex.org/C2780365114","wikidata":"https://www.wikidata.org/wiki/Q169478","display_name":"MATLAB","level":2,"score":0.6377630233764648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6107237339019775},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5372633337974548},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4766336679458618},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.45921066403388977},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4520159363746643},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3932020664215088},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3480601906776428},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2750568985939026},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22405248880386353},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic 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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/etfa.2017.8247618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2017.8247618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:kth-298572","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298572","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:kth-298572","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298572","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W100464641","https://openalex.org/W323536346","https://openalex.org/W1124727651","https://openalex.org/W1490961130","https://openalex.org/W1535712589","https://openalex.org/W1746819321","https://openalex.org/W1935773568","https://openalex.org/W1976767421","https://openalex.org/W1995711095","https://openalex.org/W1997917809","https://openalex.org/W2001842014","https://openalex.org/W2051563170","https://openalex.org/W2070745108","https://openalex.org/W2106944478","https://openalex.org/W2182626644","https://openalex.org/W2909388668","https://openalex.org/W3004784263","https://openalex.org/W4211049957","https://openalex.org/W6629361144","https://openalex.org/W6676169587","https://openalex.org/W6686072284","https://openalex.org/W6757568908"],"related_works":["https://openalex.org/W2931365531","https://openalex.org/W2357111844","https://openalex.org/W3014573403","https://openalex.org/W4381941132","https://openalex.org/W2084593435","https://openalex.org/W2114881872","https://openalex.org/W2198736978","https://openalex.org/W3084133043","https://openalex.org/W2139145565","https://openalex.org/W2905297725"],"abstract_inverted_index":{"Ventilation":[0],"is":[1,12,79,82,102,139,186],"vital":[2],"for":[3,37,111,180,194],"the":[4,27,30,45,61,106,116,121,127,171,174,184],"production":[5],"in":[6,21,29,115,118],"an":[7,69],"underground":[8,145],"mine.":[9,31],"Therefore,":[10],"it":[11],"important":[13],"to":[14,23,57,156,188],"have":[15],"efficient":[16],"and":[17,25,96,163],"accurate":[18],"design":[19,77],"tools":[20],"order":[22],"ensure":[24],"optimize":[26],"airflows":[28],"There":[32],"are":[33,154],"several":[34],"commercial":[35],"software":[36],"airflow":[38],"simulation":[39,49,56,128],"based":[40,141],"on":[41,142,170],"first":[42],"principles.":[43],"However,":[44],"computational":[46,93],"cost":[47],"of":[48,63,123,151,176],"together":[50],"with":[51,90],"integrational":[52],"obstacles":[53],"when":[54],"connecting":[55],"control":[58,99,192],"strategies":[59,193],"limits":[60],"benefit":[62],"these":[64],"tools.":[65],"In":[66],"this":[67],"paper":[68],"approach":[70],"utilizing":[71],"surrogate":[72,86,124,152,172,178,185],"models":[73,87,107,125,153,179],"as":[74,134],"a":[75,130,143,164],"complementary":[76],"tool":[78],"presented.":[80],"It":[81,101],"shown":[83,104],"that":[84,105],"using":[85,177],"one":[88],"can":[89,108],"rather":[91],"low":[92],"expense":[94],"evaluate":[95],"benchmark":[97,189],"different":[98,191],"strategies.":[100],"also":[103],"be":[109],"used":[110,140,187],"identifying":[112,181],"possible":[113],"bottlenecks":[114],"system":[117],"advance.":[119],"Moreover,":[120],"use":[122],"transfer":[126],"into":[129],"development-friendly":[131],"environment":[132],"(such":[133],"Matlab).":[135],"A":[136],"test":[137],"case":[138],"real":[144],"mine":[146,195],"ventilation":[147],"design.":[148],"Two":[149],"types":[150],"fitted":[155],"process":[157,166],"data;":[158],"multiple":[159],"least":[160],"squares":[161],"regression":[162],"Gaussian":[165],"model.":[167],"Sensitivity":[168],"analysis":[169],"shows":[173],"potential":[175],"bottlenecks.":[182],"Furthermore,":[183],"two":[190],"ventilation.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}