{"id":"https://openalex.org/W7140765936","doi":"https://doi.org/10.1016/j.engappai.2026.114628","title":"Physics-informed dynamic ensemble learning for real-time urban water quality monitoring","display_name":"Physics-informed dynamic ensemble learning for real-time urban water quality monitoring","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7140765936","doi":"https://doi.org/10.1016/j.engappai.2026.114628"},"language":"en","primary_location":{"id":"doi:10.1016/j.engappai.2026.114628","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114628","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"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":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.engappai.2026.114628","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075023462","display_name":"Renfang Wang","orcid":"https://orcid.org/0000-0002-8239-8248"},"institutions":[{"id":"https://openalex.org/I1315279114","display_name":"Zhejiang Wanli University","ror":"https://ror.org/00rjdhd62","country_code":"CN","type":"education","lineage":["https://openalex.org/I1315279114"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renfang Wang","raw_affiliation_strings":["College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo, China","institution_ids":["https://openalex.org/I1315279114"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130632514","display_name":"Xinyu Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Zhao","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ocean University of China, Qingdao, China"],"raw_orcid":"https://orcid.org/0009-0000-3712-3301","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735899","display_name":"Xiufeng Liu","orcid":"https://orcid.org/0000-0001-5133-6688"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Xiufeng Liu","raw_affiliation_strings":["Department of Technology, Management and Economics, Technical University of Denmark, Kgs. Lyngby, Denmark"],"raw_orcid":"https://orcid.org/0000-0001-5133-6688","affiliations":[{"raw_affiliation_string":"Department of Technology, Management and Economics, Technical University of Denmark, Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130635240","display_name":"Xu Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Xu Cheng","raw_affiliation_strings":["Department of Technology, Management and Economics, Technical University of Denmark, Kgs. Lyngby, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-4724-5748","affiliations":[{"raw_affiliation_string":"Department of Technology, Management and Economics, Technical University of Denmark, Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088115225","display_name":"Hong Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I1315279114","display_name":"Zhejiang Wanli University","ror":"https://ror.org/00rjdhd62","country_code":"CN","type":"education","lineage":["https://openalex.org/I1315279114"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Qiu","raw_affiliation_strings":["College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo, China","institution_ids":["https://openalex.org/I1315279114"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088115225"],"corresponding_institution_ids":["https://openalex.org/I1315279114"],"apc_list":{"value":3170,"currency":"USD","value_usd":3170},"apc_paid":{"value":3170,"currency":"USD","value_usd":3170},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68098415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"175","issue":null,"first_page":"114628","last_page":"114628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.24210000038146973,"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"}},"topics":[{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.24210000038146973,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.19009999930858612,"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"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.1720000058412552,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5471000075340271},{"id":"https://openalex.org/keywords/water-quality","display_name":"Water quality","score":0.5012000203132629},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.43880000710487366},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.39419999718666077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8661999702453613},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5471000075340271},{"id":"https://openalex.org/C2780797713","wikidata":"https://www.wikidata.org/wiki/Q625376","display_name":"Water quality","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43880000710487366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4205000102519989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3961000144481659},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.335099995136261},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.29829999804496765},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27950000762939453}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.engappai.2026.114628","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114628","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"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":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.engappai.2026.114628","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114628","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"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":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6","score":0.5704689025878906}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320328382","display_name":"Food Science and Engineering, the Most Important Discipline of Zhejiang Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W92315366","https://openalex.org/W2511707671","https://openalex.org/W2828337747","https://openalex.org/W2841842839","https://openalex.org/W2881370126","https://openalex.org/W2904551774","https://openalex.org/W2980101188","https://openalex.org/W2990765082","https://openalex.org/W2999667975","https://openalex.org/W3014468003","https://openalex.org/W3080930191","https://openalex.org/W3133294546","https://openalex.org/W3140906137","https://openalex.org/W3162612127","https://openalex.org/W3175743832","https://openalex.org/W3185095713","https://openalex.org/W3185247140","https://openalex.org/W3199344758","https://openalex.org/W3203696367","https://openalex.org/W3203878905","https://openalex.org/W4214930549","https://openalex.org/W4220760424","https://openalex.org/W4281480322","https://openalex.org/W4283725612","https://openalex.org/W4310131922","https://openalex.org/W4319443211","https://openalex.org/W4364322549","https://openalex.org/W4366778955","https://openalex.org/W4384895673","https://openalex.org/W4386961715","https://openalex.org/W4387806925","https://openalex.org/W4388672717","https://openalex.org/W4390837524","https://openalex.org/W4391311198","https://openalex.org/W4393256733","https://openalex.org/W4400645223","https://openalex.org/W4404140537","https://openalex.org/W4404645931","https://openalex.org/W4405237587","https://openalex.org/W4410909157","https://openalex.org/W4412430040"],"related_works":[],"abstract_inverted_index":{"Ensuring":[0],"high-quality":[1],"water":[2,32,89,148,172,241],"resources":[3],"is":[4],"crucial":[5],"for":[6,70,80,142,176,188],"sustainable":[7],"urban":[8,31,88,177],"development,":[9],"public":[10],"health,":[11],"and":[12,27,54,73,117,167,210,227],"resilient":[13],"city":[14,147,240],"infrastructure,":[15],"yet":[16],"traditional":[17,115],"anomaly":[18,174,189],"detection":[19,175],"methods":[20,116],"struggle":[21],"with":[22,58,157,185],"the":[23,103,164],"highly":[24],"variable,":[25],"non-stationary,":[26],"concept-drifting":[28],"nature":[29],"of":[30,96,170],"quality":[33,90,173],"data":[34],"streams.":[35],"This":[36],"study":[37],"proposes":[38],"a":[39,66,74,86,99],"Physics-Informed":[40,59],"Dynamic":[41,192],"Ensemble":[42],"Learning":[43],"(PIDEL)":[44],"framework,":[45],"an":[46,94],"artificial":[47],"intelligence":[48],"approach":[49],"that":[50,153],"combines":[51],"diverse":[52],"classical":[53],"deep":[55,186],"learning":[56,160,187],"models":[57],"Neural":[60],"Networks":[61],"(PINNs)":[62],"embedding":[63],"convection\u2013diffusion":[64],"constraints,":[65],"Genetic":[67,203],"Algorithm":[68],"(GA)":[69],"ensemble":[71,159,193],"optimization,":[72],"Jensen\u2013Shannon":[75,199],"Divergence":[76],"(JSD)":[77],"based":[78],"mechanism":[79],"dynamic":[81,158],"model":[82],"switching.":[83,201],"Applied":[84],"to":[85,114,195],"real-world":[87],"dataset,":[91],"PIDEL":[92],"achieves":[93],"F1-score":[95,209],"0.95,":[97],"representing":[98],"59%":[100,211],"improvement":[101],"over":[102],"best":[104],"static":[105],"ensemble,":[106,206],"while":[107],"reducing":[108],"false":[109],"alarms":[110],"by":[111],"73%":[112],"compared":[113],"maintaining":[118],"F1-scores":[119],"above":[120],"0.9":[121],"across":[122],"all":[123],"sliding":[124],"windows.":[125],"The":[126],"framework":[127],"processes":[128],"each":[129],"60-minute":[130],"window":[131],"in":[132,145],"approximately":[133],"2.3":[134],"s":[135,234],"on":[136],"standard":[137],"hardware,":[138],"demonstrating":[139],"its":[140],"suitability":[141],"real-time":[143],"deployment":[144],"smart":[146,239],"systems.":[149],"These":[150],"results":[151],"highlight":[152],"integrating":[154],"physics-informed":[155],"constraints":[156,184],"can":[161],"substantially":[162],"enhance":[163],"reliability,":[165],"interpretability,":[166],"operational":[168],"value":[169],"automated":[171],"utilities.":[178],"\u2022":[179,191,202,213,230],"Novel":[180],"LSTM-PINN":[181],"integrates":[182],"physics":[183,215],"detection.":[190],"adapts":[194],"concept":[196],"drift":[197],"via":[198],"divergence-based":[200],"algorithm":[204],"optimizes":[205],"achieving":[207],"95%":[208],"improvement.":[212],"Optimal":[214],"loss":[216],"coefficient":[217],"(":[218],"\u03bb":[219],"=":[220],"0":[221],".":[222],"35":[223],")":[224],"balances":[225],"physical":[226],"data-driven":[228],"learning.":[229],"Real-time":[231],"processing":[232],"(2.3":[233],"per":[235],"window)":[236],"enables":[237],"practical":[238],"monitoring.":[242]},"counts_by_year":[],"updated_date":"2026-03-28T06:11:35.319607","created_date":"2026-03-27T00:00:00"}