{"id":"https://openalex.org/W7125097645","doi":"https://doi.org/10.1016/j.ecoinf.2026.103617","title":"A comparative study of ensemble and non-ensemble machine learning methods for predicting river pollution index","display_name":"A comparative study of ensemble and non-ensemble machine learning methods for predicting river pollution index","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7125097645","doi":"https://doi.org/10.1016/j.ecoinf.2026.103617"},"language":"en","primary_location":{"id":"doi:10.1016/j.ecoinf.2026.103617","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ecoinf.2026.103617","pdf_url":null,"source":{"id":"https://openalex.org/S195809937","display_name":"Ecological Informatics","issn_l":"1574-9541","issn":["1574-9541","1878-0512"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ecological Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.ecoinf.2026.103617","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123488290","display_name":"Luisa S.R. Nogueira","orcid":null},"institutions":[{"id":"https://openalex.org/I101100930","display_name":"Universidade Federal de Juiz de Fora","ror":"https://ror.org/04yqw9c44","country_code":"BR","type":"education","lineage":["https://openalex.org/I101100930"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Luisa S.R. Nogueira","raw_affiliation_strings":["Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil","Laboratory of Applied Mathematics, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil","institution_ids":["https://openalex.org/I101100930"]},{"raw_affiliation_string":"Laboratory of Applied Mathematics, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil","institution_ids":["https://openalex.org/I101100930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123467639","display_name":"Mariana A.S. de Carvalho","orcid":null},"institutions":[{"id":"https://openalex.org/I101100930","display_name":"Universidade Federal de Juiz de Fora","ror":"https://ror.org/04yqw9c44","country_code":"BR","type":"education","lineage":["https://openalex.org/I101100930"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Mariana A.S. de Carvalho","raw_affiliation_strings":["Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil","institution_ids":["https://openalex.org/I101100930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123486196","display_name":"Berilo de O. Santos","orcid":null},"institutions":[{"id":"https://openalex.org/I101100930","display_name":"Universidade Federal de Juiz de Fora","ror":"https://ror.org/04yqw9c44","country_code":"BR","type":"education","lineage":["https://openalex.org/I101100930"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Berilo de O. Santos","raw_affiliation_strings":["Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil","Laboratory of Applied Mathematics, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil","institution_ids":["https://openalex.org/I101100930"]},{"raw_affiliation_string":"Laboratory of Applied Mathematics, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, Brazil","institution_ids":["https://openalex.org/I101100930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117839347","display_name":"Roland Yonaba","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107488","display_name":"International Institute for Water and Environmental Engineering","ror":"https://ror.org/0138r3j35","country_code":"BF","type":"education","lineage":["https://openalex.org/I4210107488"]}],"countries":["BF"],"is_corresponding":false,"raw_author_name":"Roland Yonaba","raw_affiliation_strings":["Laboratoire Eaux, Hydro-Syst\u00e8mes et Agriculture (LEHSA), Institut International d\u2019Ing\u00e9nierie de l\u2019Eau et de l\u2019Environnement (2iE), Rue de la Science - 01 POBOX 594 Ouagadougou 01, Burkina Faso"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire Eaux, Hydro-Syst\u00e8mes et Agriculture (LEHSA), Institut International d\u2019Ing\u00e9nierie de l\u2019Eau et de l\u2019Environnement (2iE), Rue de la Science - 01 POBOX 594 Ouagadougou 01, Burkina Faso","institution_ids":["https://openalex.org/I4210107488"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075793902","display_name":"Apoorva Bamal","orcid":"https://orcid.org/0000-0003-4166-6725"},"institutions":[{"id":"https://openalex.org/I188760350","display_name":"Ollscoil na Gaillimhe \u2013 University of Galway","ror":"https://ror.org/03bea9k73","country_code":"IE","type":"education","lineage":["https://openalex.org/I188760350"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Apoorva Bamal","raw_affiliation_strings":["Eco-HydroInformatics Research Group (EHIRG), Civil Engineering, University of Galway, Ireland","MaREI Research Centre, University of Galway, Ireland","Ryan Institute, University of Galway, Ireland","School of Engineering, University of Galway, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eco-HydroInformatics Research Group (EHIRG), Civil Engineering, University of Galway, Ireland","institution_ids":["https://openalex.org/I188760350"]},{"raw_affiliation_string":"MaREI Research Centre, University of Galway, Ireland","institution_ids":["https://openalex.org/I188760350"]},{"raw_affiliation_string":"Ryan Institute, University of Galway, Ireland","institution_ids":["https://openalex.org/I188760350"]},{"raw_affiliation_string":"School of Engineering, University of Galway, Ireland","institution_ids":["https://openalex.org/I188760350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059886112","display_name":"Md Galal Uddin","orcid":"https://orcid.org/0000-0001-8512-9644"},"institutions":[{"id":"https://openalex.org/I188760350","display_name":"Ollscoil na Gaillimhe \u2013 University of Galway","ror":"https://ror.org/03bea9k73","country_code":"IE","type":"education","lineage":["https://openalex.org/I188760350"]},{"id":"https://openalex.org/I4210100923","display_name":"Munster Technological University","ror":"https://ror.org/013xpqh61","country_code":"IE","type":"facility","lineage":["https://openalex.org/I4210100923"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Md Galal Uddin","raw_affiliation_strings":["Department of Civil, Structural and Environmental Engineering, Sustainable Infrastructure Research & Innovation Group, Munster Technological University, Bishopstown, Cork, Ireland","Eco-HydroInformatics Research Group (EHIRG), Civil Engineering, University of Galway, Ireland","MaREI Research Centre, University of Galway, Ireland","Ryan Institute, University of Galway, Ireland","School of Engineering, University of Galway, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil, Structural and Environmental Engineering, Sustainable Infrastructure Research & Innovation Group, Munster Technological University, Bishopstown, Cork, Ireland","institution_ids":["https://openalex.org/I4210100923"]},{"raw_affiliation_string":"Eco-HydroInformatics Research Group (EHIRG), Civil Engineering, University of Galway, Ireland","institution_ids":["https://openalex.org/I188760350"]},{"raw_affiliation_string":"MaREI Research Centre, University of Galway, Ireland","institution_ids":["https://openalex.org/I188760350"]},{"raw_affiliation_string":"Ryan Institute, University of Galway, Ireland","institution_ids":["https://openalex.org/I188760350"]},{"raw_affiliation_string":"School of Engineering, University of Galway, Ireland","institution_ids":["https://openalex.org/I188760350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019275188","display_name":"Matteo Bodini","orcid":"https://orcid.org/0000-0001-9007-6807"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Matteo Bodini","raw_affiliation_strings":["Dipartimento di Economia, Management e Metodi Quantitativi, Universit\u00e0 degli Studi di Milano, Via Conservatorio 7, 20122 Milano, Italy"],"raw_orcid":"https://orcid.org/0000-0001-9007-6807","affiliations":[{"raw_affiliation_string":"Dipartimento di Economia, Management e Metodi Quantitativi, Universit\u00e0 degli Studi di Milano, Via Conservatorio 7, 20122 Milano, Italy","institution_ids":["https://openalex.org/I189158943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121772545","display_name":"Leonardo Goliatt","orcid":null},"institutions":[{"id":"https://openalex.org/I101100930","display_name":"Universidade Federal de Juiz de Fora","ror":"https://ror.org/04yqw9c44","country_code":"BR","type":"education","lineage":["https://openalex.org/I101100930"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Leonardo Goliatt","raw_affiliation_strings":["Department of Applied and Computational Mechanics, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, MG, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied and Computational Mechanics, Federal University of Juiz de Fora, Juiz de Fora, 36036-900, MG, Brazil","institution_ids":["https://openalex.org/I101100930"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5019275188"],"corresponding_institution_ids":["https://openalex.org/I189158943"],"apc_list":{"value":2510,"currency":"USD","value_usd":2510},"apc_paid":{"value":2510,"currency":"USD","value_usd":2510},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1137673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"94","issue":null,"first_page":"103617","last_page":"103617"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.6782000064849854,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.6782000064849854,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T11634","display_name":"Water Quality and Pollution Assessment","score":0.18050000071525574,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.02019999921321869,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.7026000022888184},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.6434000134468079},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5223000049591064},{"id":"https://openalex.org/keywords/water-quality","display_name":"Water quality","score":0.5031999945640564},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5023000240325928},{"id":"https://openalex.org/keywords/water-resources","display_name":"Water resources","score":0.46459999680519104},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4453999996185303},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.43860000371932983},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.38280001282691956}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.7026000022888184},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6777999997138977},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.6434000134468079},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5687000155448914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5361999869346619},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5223000049591064},{"id":"https://openalex.org/C2780797713","wikidata":"https://www.wikidata.org/wiki/Q625376","display_name":"Water quality","level":2,"score":0.5031999945640564},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5023000240325928},{"id":"https://openalex.org/C153823671","wikidata":"https://www.wikidata.org/wiki/Q1049799","display_name":"Water resources","level":2,"score":0.46459999680519104},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.43860000371932983},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39629998803138733},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.38280001282691956},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3781999945640564},{"id":"https://openalex.org/C521259446","wikidata":"https://www.wikidata.org/wiki/Q58734","display_name":"Pollution","level":2,"score":0.357699990272522},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C2909468537","wikidata":"https://www.wikidata.org/wiki/Q58734","display_name":"Environmental pollution","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C66204764","wikidata":"https://www.wikidata.org/wiki/Q219416","display_name":"Sustainability","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3043999969959259},{"id":"https://openalex.org/C189119545","wikidata":"https://www.wikidata.org/wiki/Q5128022","display_name":"Probabilistic classification","level":4,"score":0.2948000133037567},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2696000039577484},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2531999945640564},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2508000135421753},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1016/j.ecoinf.2026.103617","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ecoinf.2026.103617","pdf_url":null,"source":{"id":"https://openalex.org/S195809937","display_name":"Ecological Informatics","issn_l":"1574-9541","issn":["1574-9541","1878-0512"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ecological Informatics","raw_type":"journal-article"},{"id":"pmh:oai:air.unimi.it:2434/1212637","is_oa":true,"landing_page_url":"https://hdl.handle.net/2434/1212637","pdf_url":null,"source":{"id":"https://openalex.org/S4306400516","display_name":"Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I189158943","host_organization_name":"University of Milan","host_organization_lineage":["https://openalex.org/I189158943"],"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":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:99e0f366719f48e8a4658206c933cd74","is_oa":true,"landing_page_url":"https://doaj.org/article/99e0f366719f48e8a4658206c933cd74","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Ecological Informatics, Vol 94, Iss , Pp 103617- (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.ecoinf.2026.103617","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ecoinf.2026.103617","pdf_url":null,"source":{"id":"https://openalex.org/S195809937","display_name":"Ecological Informatics","issn_l":"1574-9541","issn":["1574-9541","1878-0512"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ecological Informatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3387731340","display_name":null,"funder_award_id":"APQ-04458-23","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G4471807746","display_name":null,"funder_award_id":"307688/2022-4","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G4603776966","display_name":null,"funder_award_id":"APQ-02513-22","funder_id":"https://openalex.org/F4320322980","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais"},{"id":"https://openalex.org/G5893932025","display_name":null,"funder_award_id":"BPD-00083-22","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G6177886557","display_name":null,"funder_award_id":"409433/2022-5","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G6680174532","display_name":null,"funder_award_id":"304646/2025-3","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G7287677283","display_name":null,"funder_award_id":"2021 AV02 0062/22","funder_id":"https://openalex.org/F4320322904","funder_display_name":"Financiadora de Estudos e Projetos"},{"id":"https://openalex.org/G8328852853","display_name":null,"funder_award_id":"APQ-02513-22","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320322904","display_name":"Financiadora de Estudos e Projetos","ror":"https://ror.org/030w99567"},{"id":"https://openalex.org/F4320322980","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais","ror":"https://ror.org/00nc55f03"},{"id":"https://openalex.org/F4320324372","display_name":"Universidade Federal de Juiz de Fora","ror":"https://ror.org/04yqw9c44"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1963964211","https://openalex.org/W1964342857","https://openalex.org/W1967436799","https://openalex.org/W1968111533","https://openalex.org/W2010119146","https://openalex.org/W2025597305","https://openalex.org/W2093717447","https://openalex.org/W2112796928","https://openalex.org/W2336586302","https://openalex.org/W2912934387","https://openalex.org/W2948456504","https://openalex.org/W3045004532","https://openalex.org/W3094948551","https://openalex.org/W3107509627","https://openalex.org/W3108703399","https://openalex.org/W3113372098","https://openalex.org/W3154456494","https://openalex.org/W3164686837","https://openalex.org/W3177823658","https://openalex.org/W3194396378","https://openalex.org/W3201728646","https://openalex.org/W3204688550","https://openalex.org/W3211344590","https://openalex.org/W3211647702","https://openalex.org/W4205243560","https://openalex.org/W4212871224","https://openalex.org/W4225248915","https://openalex.org/W4282978935","https://openalex.org/W4283071960","https://openalex.org/W4284958113","https://openalex.org/W4286491885","https://openalex.org/W4292730325","https://openalex.org/W4296968143","https://openalex.org/W4304690709","https://openalex.org/W4310266276","https://openalex.org/W4317743691","https://openalex.org/W4323925539","https://openalex.org/W4385704330","https://openalex.org/W4386416063","https://openalex.org/W4387265043","https://openalex.org/W4392715357","https://openalex.org/W4392817873","https://openalex.org/W4392980686","https://openalex.org/W4396517949","https://openalex.org/W4396663515","https://openalex.org/W4400681382","https://openalex.org/W4400886706","https://openalex.org/W4402380434","https://openalex.org/W4402913047","https://openalex.org/W4403111311","https://openalex.org/W4404291864","https://openalex.org/W4404452232","https://openalex.org/W4405445965","https://openalex.org/W4406016889","https://openalex.org/W4406620798","https://openalex.org/W4407269854","https://openalex.org/W4407598042","https://openalex.org/W4408058560","https://openalex.org/W4408561324","https://openalex.org/W4408951074","https://openalex.org/W4408989338","https://openalex.org/W4412551751","https://openalex.org/W4413477545","https://openalex.org/W4414143337","https://openalex.org/W4415390199","https://openalex.org/W4415829087","https://openalex.org/W4416051883","https://openalex.org/W4416432315","https://openalex.org/W4416746484","https://openalex.org/W7107877164"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"prediction":[1,134,185,258],"of":[2,56,87,108,149,176,195],"river":[3,183,227],"water":[4,160,216],"quality":[5,161],"is":[6],"fundamental":[7],"to":[8,28,140,153,205,210],"environmental":[9],"sustainability":[10],"and":[11,62,67,76,121,142,174,178,191,202,209,245,269,275],"public":[12],"health,":[13],"particularly":[14,198],"amid":[15],"increasing":[16],"freshwater":[17],"scarcity.":[18],"This":[19],"study":[20,164],"develops":[21],"a":[22,36,53,85,187,224],"robust":[23,201],"Machine":[24],"Learning":[25],"(ML)":[26],"framework":[27],"forecast":[29],"the":[30,105,118,147,170,193],"River":[31],"Pollution":[32],"Index":[33],"(RPI)":[34],"using":[35],"comprehensive":[37],"36-year":[38,225],"national":[39,189],"dataset":[40,229],"from":[41,230],"Taiwan\u2019s":[42],"Environmental":[43],"Protection":[44],"Administration,":[45],"covering":[46],"over":[47,111],"500":[48],"monitoring":[49],"stations.":[50],"We":[51],"conducted":[52],"systematic":[54,171],"comparison":[55,175],"ensemble":[57,109,150,177,234],"methods":[58,238],"(CatBoost,":[59],"XGBoost,":[60],"NGBoost)":[61],"non-ensemble":[63,112,179,237,264],"benchmarks":[64],"(SVM,":[65],"ElasticNet,":[66],"1D":[68],"CNN).":[69],"Hyperparameters":[70],"were":[71],"optimized":[72],"via":[73],"Bayesian":[74,267],"optimization,":[75,173],"statistical":[77],"significance":[78],"was":[79],"ensured":[80],"by":[81,136,260],"evaluating":[82],"model":[83,273],"stabilityusing":[84],"suite":[86],"complementary":[88],"indicators":[89],"(RMSE,":[90],"MAE,":[91],"R":[92,129,250],"2":[93,130,251],",":[94],"A10":[95],"index)":[96],"across":[97],"30":[98,270],"independent":[99],"experimental":[100],"runs.":[101],"The":[102,163],"results":[103],"demonstrated":[104],"consistent":[106],"superiority":[107],"models":[110,181,222,256],"counterparts.":[113],"Among":[114],"them,":[115],"CatBoost":[116,241],"achieved":[117,242],"highest":[119],"accuracy":[120,246],"stability":[122,244],"(RMSE":[123,247],"\u2248":[124,127,248],"0.85,":[125,249],"MAE":[126],"0.61,":[128],"=":[131,252],"0.78),":[132],"reducing":[133],"error":[135,259],"approximately":[137],"20%":[138,262],"relative":[139],"SVM":[141],"ElasticNet.":[143],"These":[144],"findings":[145],"highlight":[146],"capacity":[148],"learning":[151],"techniques":[152],"capture":[154],"complex,":[155],"non-linear":[156],"interactions":[157],"inherent":[158],"in":[159,214],"data.":[162],"makes":[165],"two":[166],"principal":[167],"contributions:":[168],"(1)":[169],"implementation,":[172],"ML":[180,221],"for":[182],"pollution":[184,228],"on":[186,223],"long-term":[188],"dataset;":[190],"(2)":[192],"identification":[194],"ensemble-based":[196],"methods,":[197],"CatBoost,":[199],"as":[200],"data-driven":[203],"tools":[204],"enhance":[206],"RPI":[207],"forecasting":[208],"support":[211],"informed":[212],"decision-making":[213],"sustainable":[215],"resource":[217],"management.":[218],"\u2022":[219,232,240,254,266],"Evaluated":[220],"nationwide":[226],"Taiwan.":[231],"Compared":[233],"(CatBoost/XGBoost/NGBoost)":[235],"vs":[236],"(SVM/CNN).":[239],"superior":[243],"0.78).":[253],"Ensemble":[255],"reduced":[257],"\u223c":[261],"versus":[263],"benchmarks.":[265],"optimization":[268],"runs":[271],"validated":[272],"robustness":[274],"reliability.":[276]},"counts_by_year":[],"updated_date":"2026-01-25T23:04:38.658462","created_date":"2026-01-22T00:00:00"}
