{"id":"https://openalex.org/W7147588626","doi":"https://doi.org/10.1109/icaiic68212.2026.11454396","title":"Dynamic Operations Conditions of Industrial Gas Turbine Emissions Monitoring: XGBoost-DT-SVM Hybrid Stacked Ensemble Model","display_name":"Dynamic Operations Conditions of Industrial Gas Turbine Emissions Monitoring: XGBoost-DT-SVM Hybrid Stacked Ensemble Model","publication_year":2026,"publication_date":"2026-02-24","ids":{"openalex":"https://openalex.org/W7147588626","doi":"https://doi.org/10.1109/icaiic68212.2026.11454396"},"language":null,"primary_location":{"id":"doi:10.1109/icaiic68212.2026.11454396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic68212.2026.11454396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5107157692","display_name":"Rudy Winarto","orcid":null},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Rudy Winarto","raw_affiliation_strings":["School of Interdisciplinary Management and Technology, Institut Teknologi Sepuluh Nopember,Surabaya,Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Interdisciplinary Management and Technology, Institut Teknologi Sepuluh Nopember,Surabaya,Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132581671","display_name":"Wiwik Anggraeni","orcid":null},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Wiwik Anggraeni","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember,Department of Information Systems,Surabaya,Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember,Department of Information Systems,Surabaya,Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012595591","display_name":"Mauridhi Hery Purnomo","orcid":"https://orcid.org/0000-0002-6221-7382"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Mauridhi Hery Purnomo","raw_affiliation_strings":["Institut Teknologi Sepuluh Nopember,Department of Electrical Engineering,Surabaya,Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi Sepuluh Nopember,Department of Electrical Engineering,Surabaya,Indonesia","institution_ids":["https://openalex.org/I166843116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I166843116"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32339869,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"720","last_page":"725"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.2612999975681305,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12095","display_name":"Vehicle emissions and performance","score":0.2612999975681305,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11524","display_name":"Advanced Aircraft Design and Technologies","score":0.19259999692440033,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.12809999287128448,"subfield":{"id":"https://openalex.org/subfields/1507","display_name":"Fluid Flow and Transfer Processes"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6521999835968018},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.6129999756813049},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5746999979019165},{"id":"https://openalex.org/keywords/transient","display_name":"Transient (computer programming)","score":0.5630000233650208},{"id":"https://openalex.org/keywords/gas-turbines","display_name":"Gas turbines","score":0.5565999746322632},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.49309998750686646}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6521999835968018},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.6129999756813049},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5746999979019165},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.5630000233650208},{"id":"https://openalex.org/C2987684023","wikidata":"https://www.wikidata.org/wiki/Q193470","display_name":"Gas turbines","level":2,"score":0.5565999746322632},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.49309998750686646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.492900013923645},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4887000024318695},{"id":"https://openalex.org/C2778449969","wikidata":"https://www.wikidata.org/wiki/Q130760","display_name":"Turbine","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.335999995470047},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.32429999113082886},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27300000190734863},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic68212.2026.11454396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic68212.2026.11454396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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":17,"referenced_works":["https://openalex.org/W2004196017","https://openalex.org/W2050548594","https://openalex.org/W2149706766","https://openalex.org/W2295598076","https://openalex.org/W3130113818","https://openalex.org/W3156368563","https://openalex.org/W4226017353","https://openalex.org/W4229336376","https://openalex.org/W4322102682","https://openalex.org/W4385778469","https://openalex.org/W4389312871","https://openalex.org/W4392619789","https://openalex.org/W4393036190","https://openalex.org/W4395450713","https://openalex.org/W4400580628","https://openalex.org/W4405271714","https://openalex.org/W4410537458"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"emission":[1],"prediction":[2],"is":[3],"essential":[4],"for":[5],"maintaining":[6],"regulatory":[7],"compliance":[8],"and":[9,27,44,58,74,97,112,119,132,143],"optimizing":[10],"industrial":[11,103],"gas":[12],"turbine":[13],"performance.":[14],"Conventional":[15],"Predictive":[16],"Emissions":[17,137],"Monitoring":[18,138],"System":[19,139],"(PEMS)":[20],"often":[21],"exhibit":[22],"reduced":[23],"accuracy":[24],"under":[25,117],"dynamic":[26],"nonlinear":[28],"operating":[29],"conditions.":[30,122],"This":[31],"study":[32],"introduces":[33],"a":[34,130],"hybrid":[35],"stacked":[36,81],"ensemble":[37,82,128],"framework":[38],"that":[39,79],"integrates":[40],"XGBoost,":[41],"Decision":[42],"Tree,":[43],"Support":[45],"Vector":[46],"Machine":[47],"base":[48],"learners":[49],"with":[50],"an":[51,88],"ElasticNet":[52,107],"meta-learner":[53,108],"to":[54,135],"enhance":[55],"robustness,":[56],"accuracy,":[57],"computational":[59],"efficiency.":[60],"Using":[61],"cleaned":[62],"operational":[63],"datasets,":[64],"the":[65,80,126],"model":[66],"predicts":[67],"four":[68],"key":[69],"pollutants:":[70],"CO,":[71],"CO2,":[72],"SO2,":[73],"NO.":[75],"Experimental":[76],"results":[77],"show":[78],"consistently":[83],"outperforms":[84],"individual":[85],"learners,":[86],"achieving":[87],"average":[89],"coefficient":[90],"of":[91,94],"determination":[92],"($\\mathrm{R}^{2}$)":[93],"approximately":[95],"0.95":[96],"MAPE":[98],"values":[99],"below":[100],"5%,":[101],"meeting":[102],"acceptance":[104],"criteria.":[105],"The":[106,123],"further":[109],"improves":[110],"generalization":[111],"reduces":[113],"error":[114],"variability,":[115],"particularly":[116],"transient":[118],"fluctuating":[120],"load":[121],"findings":[124],"highlight":[125],"XGBoost-DT-SVM":[127],"as":[129],"cost-effective":[131],"regulation-aligned":[133],"alternative":[134],"Continuous":[136],"(CEMS),":[140],"advancing":[141],"intelligent":[142],"adaptive":[144],"data-driven":[145],"PEMS":[146],"architectures.":[147]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-04-02T00:00:00"}