{"id":"https://openalex.org/W2761485808","doi":"https://doi.org/10.1109/ccta.2017.8062659","title":"Experimental study on sparse modeling of a diesel engine air path system","display_name":"Experimental study on sparse modeling of a diesel engine air path system","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2761485808","doi":"https://doi.org/10.1109/ccta.2017.8062659","mag":"2761485808"},"language":"en","primary_location":{"id":"doi:10.1109/ccta.2017.8062659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccta.2017.8062659","pdf_url":null,"source":{"id":"https://openalex.org/S4306498159","display_name":"2017 IEEE Conference on Control Technology and Applications (CCTA)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Conference on Control Technology and Applications (CCTA)","raw_type":"proceedings-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/A5032348084","display_name":"Kazuhiro Shimizu","orcid":"https://orcid.org/0000-0001-9896-0939"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhiro Shimizu","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049229051","display_name":"Hayato Nakada","orcid":null},"institutions":[{"id":"https://openalex.org/I4210137853","display_name":"Toyota Motor Corporation (Japan)","ror":"https://ror.org/02zqm6r10","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4210137853"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hayato Nakada","raw_affiliation_strings":["Toyota Motor Corporation, Higashifuji Technical Center, Susono, Shizuoka, japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyota Motor Corporation, Higashifuji Technical Center, Susono, Shizuoka, japan","institution_ids":["https://openalex.org/I4210137853"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066521241","display_name":"Kenji Kashima","orcid":"https://orcid.org/0000-0002-2963-2584"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kenji Kashima","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto, Japan","institution_ids":["https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5441,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51922299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"39","issue":null,"first_page":"1426","last_page":"1431"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9977999925613403,"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":0.9969000220298767,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9926999807357788,"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/diesel-engine","display_name":"Diesel engine","score":0.6424891948699951},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6347361207008362},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5593715906143188},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5367504358291626},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.5356200933456421},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5041252374649048},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4837070107460022},{"id":"https://openalex.org/keywords/automotive-engine","display_name":"Automotive engine","score":0.43094608187675476},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4305815100669861},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.4294394254684448},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.4164677560329437},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.41117414832115173},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.344191312789917},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3420335054397583},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33492013812065125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33363401889801025},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.33070608973503113},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22518840432167053},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19965949654579163},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.15944132208824158},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10201293230056763},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.09978356957435608},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.0709538459777832}],"concepts":[{"id":"https://openalex.org/C2780804531","wikidata":"https://www.wikidata.org/wiki/Q174174","display_name":"Diesel engine","level":2,"score":0.6424891948699951},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6347361207008362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5593715906143188},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5367504358291626},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.5356200933456421},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5041252374649048},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4837070107460022},{"id":"https://openalex.org/C56238396","wikidata":"https://www.wikidata.org/wiki/Q4056355","display_name":"Automotive engine","level":2,"score":0.43094608187675476},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4305815100669861},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.4294394254684448},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.4164677560329437},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.41117414832115173},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.344191312789917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3420335054397583},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33492013812065125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33363401889801025},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.33070608973503113},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22518840432167053},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19965949654579163},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.15944132208824158},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10201293230056763},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.09978356957435608},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0709538459777832},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccta.2017.8062659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccta.2017.8062659","pdf_url":null,"source":{"id":"https://openalex.org/S4306498159","display_name":"2017 IEEE Conference on Control Technology and Applications (CCTA)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Conference on Control Technology and Applications (CCTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1508702903","https://openalex.org/W1976709621","https://openalex.org/W2075282722","https://openalex.org/W2079356082","https://openalex.org/W2092766760","https://openalex.org/W2099272284","https://openalex.org/W2296616510","https://openalex.org/W2513607878","https://openalex.org/W2594639291","https://openalex.org/W4246840991","https://openalex.org/W4250955649","https://openalex.org/W4285719527","https://openalex.org/W6630526313"],"related_works":["https://openalex.org/W3086618278","https://openalex.org/W16274429","https://openalex.org/W2006100586","https://openalex.org/W4300809132","https://openalex.org/W2103373899","https://openalex.org/W2367223136","https://openalex.org/W2039972010","https://openalex.org/W2796568981","https://openalex.org/W2741862378","https://openalex.org/W2115519811"],"abstract_inverted_index":{"Toward":[0],"model-based":[1],"development":[2],"of":[3,32,71,80],"automotive":[4],"engines,":[5],"it":[6],"is":[7],"crucial":[8],"to":[9,14,77],"develop":[10],"an":[11,26],"effective":[12],"method":[13],"construct":[15],"their":[16,47],"accurate":[17],"and":[18,45],"low-complexity":[19],"models.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24,40,75],"conduct":[25],"experimental":[27],"study":[28],"on":[29],"sparse":[30],"modeling":[31],"a":[33,56],"diesel":[34],"engine":[35],"air":[36],"path":[37],"system.":[38],"First,":[39],"apply":[41],"two":[42],"standard":[43],"methods":[44,82],"examine":[46],"trade-offs;":[48],"the":[49,59,69,84],"Gaussian":[50],"process":[51],"regression":[52,65],"that":[53,66],"can":[54,67],"provide":[55],"confidence":[57],"interval;":[58],"\u2113":[60],"<sup":[61],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[62],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[63],"-regularized":[64],"reduce":[68],"number":[70],"basis":[72],"functions.":[73],"Next,":[74],"attempt":[76],"take":[78],"advantages":[79],"both":[81],"via":[83],"so-called":[85],"Relevant":[86],"Vector":[87],"Machine.":[88]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}