{"id":"https://openalex.org/W4313203592","doi":"https://doi.org/10.1109/tie.2022.3231246","title":"Nitrogen Oxides Concentration Estimation of Diesel Engines Based on a Sparse Nonstationary Trigonometric Gaussian Process Regression With Maximizing the Composite Likelihood","display_name":"Nitrogen Oxides Concentration Estimation of Diesel Engines Based on a Sparse Nonstationary Trigonometric Gaussian Process Regression With Maximizing the Composite Likelihood","publication_year":2022,"publication_date":"2022-12-28","ids":{"openalex":"https://openalex.org/W4313203592","doi":"https://doi.org/10.1109/tie.2022.3231246"},"language":"en","primary_location":{"id":"doi:10.1109/tie.2022.3231246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2022.3231246","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Electronics","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/A5071259038","display_name":"Haojie Huang","orcid":"https://orcid.org/0000-0002-9473-4851"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I62318514","display_name":"University of Duisburg-Essen","ror":"https://ror.org/04mz5ra38","country_code":"DE","type":"education","lineage":["https://openalex.org/I62318514"]}],"countries":["CN","DE"],"is_corresponding":false,"raw_author_name":"Haojie Huang","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China","Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Duisburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-9473-4851","affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]},{"raw_affiliation_string":"Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Duisburg, Germany","institution_ids":["https://openalex.org/I62318514"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067183406","display_name":"Xin Peng","orcid":"https://orcid.org/0000-0001-9277-8415"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Peng","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9277-8415","affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053118687","display_name":"Wei Du","orcid":"https://orcid.org/0000-0001-8678-8844"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Du","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046071840","display_name":"Steven X. Ding","orcid":"https://orcid.org/0000-0002-5149-5918"},"institutions":[{"id":"https://openalex.org/I62318514","display_name":"University of Duisburg-Essen","ror":"https://ror.org/04mz5ra38","country_code":"DE","type":"education","lineage":["https://openalex.org/I62318514"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Steven X. Ding","raw_affiliation_strings":["Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Duisburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5149-5918","affiliations":[{"raw_affiliation_string":"Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Duisburg, Germany","institution_ids":["https://openalex.org/I62318514"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040197045","display_name":"Weimin Zhong","orcid":"https://orcid.org/0000-0002-4285-4739"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I62318514","display_name":"University of Duisburg-Essen","ror":"https://ror.org/04mz5ra38","country_code":"DE","type":"education","lineage":["https://openalex.org/I62318514"]}],"countries":["CN","DE"],"is_corresponding":false,"raw_author_name":"Weimin Zhong","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China","Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Duisburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-4285-4739","affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]},{"raw_affiliation_string":"Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Duisburg, Germany","institution_ids":["https://openalex.org/I62318514"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1975,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.4347629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"70","issue":"11","first_page":"11744","last_page":"11753"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.98580002784729,"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":0.9467999935150146,"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/kriging","display_name":"Kriging","score":0.8956348896026611},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.678134024143219},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6590651273727417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4933229982852936},{"id":"https://openalex.org/keywords/ground-penetrating-radar","display_name":"Ground-penetrating radar","score":0.4862036108970642},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4833609461784363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4746818244457245},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.46950292587280273},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4190514087677002},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3683755397796631},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34264177083969116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2713959217071533},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2126583755016327},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.15771141648292542}],"concepts":[{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.8956348896026611},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.678134024143219},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6590651273727417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4933229982852936},{"id":"https://openalex.org/C71813955","wikidata":"https://www.wikidata.org/wiki/Q503560","display_name":"Ground-penetrating radar","level":3,"score":0.4862036108970642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4833609461784363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4746818244457245},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.46950292587280273},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4190514087677002},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3683755397796631},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34264177083969116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2713959217071533},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2126583755016327},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.15771141648292542},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tie.2022.3231246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2022.3231246","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G1701155033","display_name":null,"funder_award_id":"61890930-3","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2362273132","display_name":null,"funder_award_id":"62173145","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W824892955","https://openalex.org/W1512149552","https://openalex.org/W1702387805","https://openalex.org/W1897171481","https://openalex.org/W2099768828","https://openalex.org/W2123687908","https://openalex.org/W2144533338","https://openalex.org/W2144902422","https://openalex.org/W2170912685","https://openalex.org/W2621841909","https://openalex.org/W2766784949","https://openalex.org/W2792351009","https://openalex.org/W2946007918","https://openalex.org/W2956844504","https://openalex.org/W2964593120","https://openalex.org/W2969500414","https://openalex.org/W2977291151","https://openalex.org/W3000508506","https://openalex.org/W3121821685","https://openalex.org/W3137528467","https://openalex.org/W3196083540","https://openalex.org/W3215564387","https://openalex.org/W3215914560","https://openalex.org/W4211049957","https://openalex.org/W4283809986","https://openalex.org/W4286890950","https://openalex.org/W4297629922","https://openalex.org/W4297781849","https://openalex.org/W4297813703","https://openalex.org/W4299802404","https://openalex.org/W6623222773","https://openalex.org/W6630718072","https://openalex.org/W6637338928","https://openalex.org/W6639724578","https://openalex.org/W6674989108","https://openalex.org/W6678165021","https://openalex.org/W6681302627","https://openalex.org/W6717592239","https://openalex.org/W6740718799","https://openalex.org/W6750067904","https://openalex.org/W6787631046","https://openalex.org/W6802505584"],"related_works":["https://openalex.org/W2141609920","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4286748465","https://openalex.org/W3118984993","https://openalex.org/W2144336328","https://openalex.org/W3196933554","https://openalex.org/W4294619368","https://openalex.org/W4380558509","https://openalex.org/W4300066510"],"abstract_inverted_index":{"Gaussian":[0],"process":[1],"regression":[2],"(GPR)":[3],"has":[4,14,29],"been":[5],"a":[6,30,64,69,81,91,107],"popular":[7],"Bayesian":[8],"method":[9,104],"for":[10],"nonlinear":[11],"fitting.":[12],"It":[13],"the":[15,26,58,78,102,111],"advantage":[16],"of":[17,43],"predictive":[18],"capability,":[19],"uncertainty":[20],"measurement,":[21],"and":[22,96],"interpretable":[23],"structure.":[24],"However,":[25],"original":[27],"GPR":[28,45,67],"heavy":[31],"complexity,":[32],"which":[33],"limits":[34],"its":[35],"effectiveness":[36],"on":[37,90,110],"Big":[38],"Data":[39],"problems.":[40],"Though":[41],"plenty":[42],"sparse":[44,66],"methods":[46],"were":[47],"proposed":[48,75,103],"to":[49,76,85],"deal":[50],"with":[51,68],"it,":[52],"they":[53],"usually":[54],"result":[55],"in":[56,80],"reducing":[57],"prediction":[59],"accuracy.":[60],"In":[61],"this":[62],"article,":[63],"novel":[65],"newly":[70],"defined":[71],"objective":[72],"function":[73],"is":[74],"obtain":[77],"hyperparameters":[79],"different":[82],"manner":[83],"compared":[84],"traditional":[86],"maximizing-likelihood.":[87],"Experimental":[88],"results":[89],"real":[92],"diesel":[93],"engine":[94],"dataset":[95],"several":[97],"public":[98],"datasets":[99],"verify":[100],"that":[101],"can":[105],"have":[106],"better":[108],"performance":[109],"prediction.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}