{"id":"https://openalex.org/W7203607940","doi":"https://doi.org/10.1038/s41598-026-65541-1","title":"CrayStack ensemble machine learning for predicting engine performance and emissions of multiple feedstock biodiesel blends with CaO-Al2O3 nanoparticles","display_name":"CrayStack ensemble machine learning for predicting engine performance and emissions of multiple feedstock biodiesel blends with CaO-Al2O3 nanoparticles","publication_year":2026,"publication_date":"2026-08-17","ids":{"openalex":"https://openalex.org/W7203607940","doi":"https://doi.org/10.1038/s41598-026-65541-1"},"language":"en","primary_location":{"id":"doi:10.1038/s41598-026-65541-1","doi":"https://doi.org/10.1038/s41598-026-65541-1","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-65541-1","pdf_url":"https://www.nature.com/articles/s41598-026-65541-1_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","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":"Scientific Reports","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.nature.com/articles/s41598-026-65541-1_reference.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5147361828","display_name":"Ajith B S","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405272456","display_name":"Sahyadri College of Engineering & Management","ror":"https://ror.org/046nvwr28","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405272456"]},{"id":"https://openalex.org/I65674248","display_name":"Visvesvaraya Technological University","ror":"https://ror.org/00ha14p11","country_code":"IN","type":"education","lineage":["https://openalex.org/I65674248"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ajith B S","raw_affiliation_strings":["Department of Mechanical Engineering, Sahyadri College of Engineering & Management, Mangaluru, Visvesvaraya Technological University, Belagavi, 590018, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Sahyadri College of Engineering & Management, Mangaluru, Visvesvaraya Technological University, Belagavi, 590018, Karnataka, India","institution_ids":["https://openalex.org/I4405272456","https://openalex.org/I65674248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108144497","display_name":"Manjunath Patel G C","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405272456","display_name":"Sahyadri College of Engineering & Management","ror":"https://ror.org/046nvwr28","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405272456"]},{"id":"https://openalex.org/I65674248","display_name":"Visvesvaraya Technological University","ror":"https://ror.org/00ha14p11","country_code":"IN","type":"education","lineage":["https://openalex.org/I65674248"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Manjunath Patel G C","raw_affiliation_strings":["Department of Mechanical Engineering, Sahyadri College of Engineering & Management, Mangaluru, Visvesvaraya Technological University, Belagavi, 590018, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Sahyadri College of Engineering & Management, Mangaluru, Visvesvaraya Technological University, Belagavi, 590018, Karnataka, India","institution_ids":["https://openalex.org/I4405272456","https://openalex.org/I65674248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022754860","display_name":"Rathishchandra Ramachandra Gatti","orcid":"https://orcid.org/0000-0002-4086-2778","observed_orcids":["https://orcid.org/0000-0002-4086-2778"]},"institutions":[{"id":"https://openalex.org/I4405272456","display_name":"Sahyadri College of Engineering & Management","ror":"https://ror.org/046nvwr28","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405272456"]},{"id":"https://openalex.org/I65674248","display_name":"Visvesvaraya Technological University","ror":"https://ror.org/00ha14p11","country_code":"IN","type":"education","lineage":["https://openalex.org/I65674248"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rathishchandra Ramachandra Gatti","raw_affiliation_strings":["Department of Mechanical Engineering, Sahyadri College of Engineering & Management, Mangaluru, Visvesvaraya Technological University, Belagavi, 590018, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Sahyadri College of Engineering & Management, Mangaluru, Visvesvaraya Technological University, Belagavi, 590018, Karnataka, India","institution_ids":["https://openalex.org/I4405272456","https://openalex.org/I65674248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017597806","display_name":"B. V. Poornima","orcid":"https://orcid.org/0000-0003-1270-6329","observed_orcids":["https://orcid.org/0000-0003-1270-6329"]},"institutions":[{"id":"https://openalex.org/I4405272456","display_name":"Sahyadri College of Engineering & Management","ror":"https://ror.org/046nvwr28","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405272456"]},{"id":"https://openalex.org/I65674248","display_name":"Visvesvaraya Technological University","ror":"https://ror.org/00ha14p11","country_code":"IN","type":"education","lineage":["https://openalex.org/I65674248"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Poornima B V","raw_affiliation_strings":["Department of Computer Science & Engineering, Sahyadri College of Engineering & Management, Mangaluru, Visvesvaraya Technological University, Belagavi, 590018, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Sahyadri College of Engineering & Management, Mangaluru, Visvesvaraya Technological University, Belagavi, 590018, Karnataka, India","institution_ids":["https://openalex.org/I4405272456","https://openalex.org/I65674248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007110521","display_name":"Olusegun David Samuel","orcid":"https://orcid.org/0000-0002-6625-2820","observed_orcids":["https://orcid.org/0000-0002-6625-2820"]},"institutions":[{"id":"https://openalex.org/I891860020","display_name":"Federal University of Petroleum Resource Effurun","ror":"https://ror.org/04ndqkb04","country_code":"NG","type":"education","lineage":["https://openalex.org/I891860020"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Olusegun David Samuel","raw_affiliation_strings":["Department of Mechanical Engineering, Federal University of Petroleum Resources, P.M.B 1221, Effurun, Delta State, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Federal University of Petroleum Resources, P.M.B 1221, Effurun, Delta State, Nigeria","institution_ids":["https://openalex.org/I891860020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147347443","display_name":"Harsha H M","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405256143","display_name":"GM University Davanagere Karnataka","ror":"https://ror.org/03tmbn325","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405256143"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Harsha H M","raw_affiliation_strings":["Department of Mechanical Engineering, GM University, Davangere,  577006, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, GM University, Davangere,  577006, India","institution_ids":["https://openalex.org/I4405256143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5136948944","display_name":"Gautham Jeppu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Gautham Jeppu","raw_affiliation_strings":["Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5108144497","https://openalex.org/A5136948944"],"corresponding_institution_ids":["https://openalex.org/I164861460","https://openalex.org/I4405272456","https://openalex.org/I65674248"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10507","display_name":"Biodiesel Production and Applications","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2103","display_name":"Fuel Technology"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10507","display_name":"Biodiesel Production and Applications","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2103","display_name":"Fuel Technology"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.00039999998989515007,"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"}},{"id":"https://openalex.org/T13990","display_name":"Engine and Fuel Emissions","score":9.999999747378752e-05,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/biodiesel-blends","display_name":"biodiesel blends","score":0.8399999737739563},{"id":"https://openalex.org/keywords/engine-performance-prediction","display_name":"engine performance prediction","score":0.8309999704360962},{"id":"https://openalex.org/keywords/crayfish-optimization-algorithm","display_name":"crayfish optimization algorithm","score":0.9769999980926514},{"id":"https://openalex.org/keywords/gaussian-process-regression","display_name":"Gaussian process regression","score":0.7749999761581421},{"id":"https://openalex.org/keywords/least-squares-boosting","display_name":"least squares boosting","score":0.9330000281333923},{"id":"https://openalex.org/keywords/support-vector-regression","display_name":"support vector regression","score":1.0},{"id":"https://openalex.org/keywords/garcinia-gummi-gutta","display_name":"Garcinia gummi-gutta","score":0.8740000128746033},{"id":"https://openalex.org/keywords/garcinia-indica","display_name":"Garcinia indica","score":1.0},{"id":"https://openalex.org/keywords/monte-carlo-simulation","display_name":"Monte Carlo simulation","score":0.8849999904632568},{"id":"https://openalex.org/keywords/probabilistic-forecasting","display_name":"probabilistic forecasting","score":0.5699999928474426}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6032000184059143},{"id":"https://openalex.org/C52896960","wikidata":"https://www.wikidata.org/wiki/Q167947","display_name":"Biodiesel","level":3,"score":0.5565999746322632},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5565000176429749},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5485000014305115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5383999943733215},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4724999964237213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4404999911785126},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.41999998688697815},{"id":"https://openalex.org/C206139338","wikidata":"https://www.wikidata.org/wiki/Q192355","display_name":"Raw material","level":2,"score":0.4115000069141388},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.38429999351501465},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.35569998621940613},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C206041023","wikidata":"https://www.wikidata.org/wiki/Q1751970","display_name":"Wilcoxon signed-rank test","level":3,"score":0.31360000371932983},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C105923489","wikidata":"https://www.wikidata.org/wiki/Q133235","display_name":"Combustion","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C53991642","wikidata":"https://www.wikidata.org/wiki/Q128991","display_name":"Biofuel","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.2838999927043915},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.27549999952316284},{"id":"https://openalex.org/C50406533","wikidata":"https://www.wikidata.org/wiki/Q1452104","display_name":"Thermal efficiency","level":3,"score":0.272599995136261},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C145828037","wikidata":"https://www.wikidata.org/wiki/Q17086219","display_name":"Least squares support vector machine","level":3,"score":0.26919999718666077},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C103697071","wikidata":"https://www.wikidata.org/wiki/Q39558","display_name":"Gasoline","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C68189081","wikidata":"https://www.wikidata.org/wiki/Q12748","display_name":"Fossil fuel","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s41598-026-65541-1","doi":"https://doi.org/10.1038/s41598-026-65541-1","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-65541-1","pdf_url":"https://www.nature.com/articles/s41598-026-65541-1_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","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":"Scientific Reports","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s41598-026-65541-1","doi":"https://doi.org/10.1038/s41598-026-65541-1","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-65541-1","pdf_url":"https://www.nature.com/articles/s41598-026-65541-1_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","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":"Scientific Reports","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9853000044822693,"display_name":"Affordable and clean energy"},{"id":"https://metadata.un.org/sdg/9","score":0.6773999929428101,"display_name":"Industry, innovation and infrastructure"},{"id":"https://metadata.un.org/sdg/12","score":0.5925999879837036,"display_name":"Responsible consumption and production"},{"id":"https://metadata.un.org/sdg/13","score":0.5351999998092651,"display_name":"Climate action"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7203607940.pdf","grobid_xml":"https://content.openalex.org/works/W7203607940.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7222827630","https://openalex.org/W7221795468","https://openalex.org/W7128737039","https://openalex.org/W4412616756","https://openalex.org/W7169672338","https://openalex.org/W7221459639","https://openalex.org/W7128988260","https://openalex.org/W4416226347","https://openalex.org/W7164888642","https://openalex.org/W7124582970"],"abstract_inverted_index":{"Abstract":[0],"The":[1,35,225,242],"global":[2],"transition":[3],"toward":[4],"sustainable":[5,358],"energy":[6],"has":[7],"positioned":[8],"multi-oil":[9],"feedstocks":[10],"(Garcinia":[11],"gummi-gutta":[12],"and":[13,31,65,73,85,101,112,117,145,216,218,255,271,299,306,326,332,345],"Garcinia":[14],"indica)":[15],"to":[16,23,90,189,351],"increase":[17],"feedstock":[18],"availability,":[19],"which":[20,132],"is":[21],"vital":[22],"biodiesel":[24,45,48],"production,":[25],"thereby":[26],"reducing":[27],"fossil":[28],"fuel":[29,62,94],"dependencies":[30],"limiting":[32],"harmful":[33],"emissions.":[34],"incorporation":[36],"of":[37,93,109,200,264,297,302,319,356],"multifunctional":[38],"CaO-Al":[39],"2":[40],"O":[41],"3":[42],"nanoparticles":[43,102],"into":[44],"further":[46],"enhances":[47],"combustion":[49],"characteristics.":[50],"However,":[51],"predicting":[52],"an":[53,105,315],"engine":[54,113,330],"performance":[55,331],"(brake":[56],"thermal":[57],"efficiency:":[58],"BTE,":[59,213],"brake":[60],"specific":[61],"consumption:":[63],"BSFC)":[64],"emissions":[66],"(carbon":[67],"monoxide:":[68],"CO,":[69,215],"unburnt":[70],"hydrocarbon:":[71],"UHC,":[72],"nitrogen":[74],"oxide:":[75],"NOx)":[76],"remains":[77],"a":[78,127,150,183,347],"critical":[79],"bottleneck":[80],"for":[81,212,221,223,238,328],"currently":[82],"practiced":[83],"traditional":[84],"resource-intensive":[86],"experimental":[87,177,340],"methods":[88],"due":[89],"complex":[91],"interplay":[92],"properties":[95],"(biodiesel":[96],"blends:":[97],"B10,":[98],"B20,":[99],"B30,":[100],"concentration":[103],"possessing":[104],"average":[106,316],"particle":[107],"size":[108],"75.4":[110],"nm)":[111],"variables":[114],"(engine":[115],"load":[116],"compression":[118],"ratio).":[119],"To":[120],"bridge":[121],"this":[122,124],"gap,":[123],"study":[125],"used":[126],"CrayStack":[128,193,233,243,275,312,337],"machine":[129],"learning":[130],"ensemble,":[131],"integrates":[133],"three":[134,201,288],"diverse":[135],"base":[136,202,289],"learners\u2014Gaussian":[137],"Process":[138],"Regression":[139,148],"(GPR),":[140],"Least":[141],"Squares":[142],"Boosting":[143],"(LSBoost),":[144],"Support":[146],"Vector":[147],"(SVR)\u2014with":[149],"meta-learner":[151],"whose":[152],"ensemble":[153,194,234,244,313],"weights":[154],"are":[155],"dynamically":[156],"optimized":[157],"via":[158],"the":[159,192,198,207,232,256,293,353],"cutting-edge":[160],"Crayfish":[161],"Optimization":[162],"Algorithm":[163],"(COA).":[164],"This":[165],"nature-inspired":[166],"optimization":[167],"method":[168],"uniquely":[169],"captures":[170],"complex,":[171],"multi-response":[172],"nonlinearities":[173],"using":[174],"highly":[175],"constrained":[176],"datasets":[178],"(25":[179],"training,":[180],"10":[181],"testing),":[182],"task":[184],"that":[185,231,285],"conventional":[186],"models":[187],"fail":[188],"perform.":[190],"In":[191],"framework,":[195],"COA":[196],"evaluates":[197],"contributions":[199],"learners,":[203],"with":[204,249,277,292],"GPR":[205,267],"having":[206],"highest":[208],"contribution":[209],"(>":[210],"50%)":[211],"BSFC,":[214],"NOx,":[217],"LSBoost":[219,272],"accounting":[220],"52.3%":[222],"UHC.":[224],"Pairwise":[226],"Wilcoxon":[227],"single-ranked":[228],"analysis":[229],"confirmed":[230],"consistently":[235,286],"outperformed":[236],"SVR":[237,269],"all":[239,253,310],"five":[240],"responses.":[241,311],"demonstrated":[245],"superior":[246],"predictive":[247],"performance,":[248],"consistent":[250],"results":[251],"across":[252,309],"responses":[254],"lowest":[257,294],"composite":[258],"Mean":[259],"Absolute":[260],"Percentage":[261],"Error":[262],"(MAPE)":[263],"4.38%,":[265],"outperforming":[266],"(4.93%),":[268],"(6.01%),":[270],"(7.70%).":[273],"Integrating":[274],"Ensemble":[276],"Monte":[278],"Carlo":[279],"simulations":[280],"(MCS)":[281],"yields":[282],"probabilistic":[283],"predictions":[284,308],"outperform":[287],"learner":[290],"models,":[291],"error":[295],"(RMSE":[296],"0.35":[298],"standard":[300],"deviation":[301],"0.02),":[303],"ensuring":[304],"robust":[305],"reliable":[307],"requires":[314],"computational":[317,323],"time":[318],"3.736s,":[320],"demonstrating":[321],"its":[322],"efficiency,":[324],"robustness,":[325],"reliability":[327],"accurate":[329],"emission":[333],"prediction":[334],"applications.":[335],"Thereby,":[336],"drastically":[338],"eliminated":[339],"overhead":[341],"(cost,":[342],"power,":[343],"materials)":[344],"provided":[346],"transformative,":[348],"scalable":[349],"tool":[350],"accelerate":[352],"commercial":[354],"deployment":[355],"nanoparticle-enhanced":[357],"biofuel":[359],"blends.":[360]},"counts_by_year":[],"updated_date":"2026-09-22T17:25:34.749102","created_date":"2026-08-18T00:00:00"}