{"id":"https://openalex.org/W7225736151","doi":"https://doi.org/10.21203/rs.3.rs-11382325/v1","title":"Transfer learning-enhanced physics-informed neural networks for efficient simulation of river flood in complex large-scale river systems","display_name":"Transfer learning-enhanced physics-informed neural networks for efficient simulation of river flood in complex large-scale river systems","publication_year":2026,"publication_date":"2026-11-10","ids":{"openalex":"https://openalex.org/W7225736151","doi":"https://doi.org/10.21203/rs.3.rs-11382325/v1"},"language":"en","primary_location":{"id":"doi:10.21203/rs.3.rs-11382325/v1","doi":"https://doi.org/10.21203/rs.3.rs-11382325/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11382325/v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21203/rs.3.rs-11382325/v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122710190","display_name":"Kang Zheng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210092032","display_name":"China Institute of Water Resources and Hydropower Research","ror":"https://ror.org/00m4czf33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Zheng","raw_affiliation_strings":["China Institute of Water Resources and Hydropower Research"],"raw_orcid":"https://orcid.org/0009-0000-0603-9131","affiliations":[{"raw_affiliation_string":"China Institute of Water Resources and Hydropower Research","institution_ids":["https://openalex.org/I4210092032"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161377254","display_name":"Xin Qi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210092032","display_name":"China Institute of Water Resources and Hydropower Research","ror":"https://ror.org/00m4czf33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Qi","raw_affiliation_strings":["China Institute of Water Resources and Hydropower Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Institute of Water Resources and Hydropower Research","institution_ids":["https://openalex.org/I4210092032"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161390937","display_name":"Dawei Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210092032","display_name":"China Institute of Water Resources and Hydropower Research","ror":"https://ror.org/00m4czf33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Zhang","raw_affiliation_strings":["China Institute of Water Resources and Hydropower Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Institute of Water Resources and Hydropower Research","institution_ids":["https://openalex.org/I4210092032"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147731772","display_name":"Xinzheng FENG","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210092032","display_name":"China Institute of Water Resources and Hydropower Research","ror":"https://ror.org/00m4czf33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinzheng Feng","raw_affiliation_strings":["China Institute of Water Resources and Hydropower Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Institute of Water Resources and Hydropower Research","institution_ids":["https://openalex.org/I4210092032"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5161413692","display_name":"Weiqi Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210092032","display_name":"China Institute of Water Resources and Hydropower Research","ror":"https://ror.org/00m4czf33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiqi Wang","raw_affiliation_strings":["China Institute of Water Resources and Hydropower Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Institute of Water Resources and Hydropower Research","institution_ids":["https://openalex.org/I4210092032"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210092032"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.8500999808311462,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.8500999808311462,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.13770000636577606,"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/T10930","display_name":"Flood Risk Assessment and Management","score":0.005499999970197678,"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"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C74256435","wikidata":"https://www.wikidata.org/wiki/Q134052","display_name":"Flood myth","level":2,"score":0.8019000291824341},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7829999923706055},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.667900025844574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5954999923706055},{"id":"https://openalex.org/C2992143177","wikidata":"https://www.wikidata.org/wiki/Q7973862","display_name":"Water transfer","level":2,"score":0.5400000214576721},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.49729999899864197},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.47679999470710754},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.38679999113082886},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3862000107765198},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C183195422","wikidata":"https://www.wikidata.org/wiki/Q3409303","display_name":"Flood forecasting","level":3,"score":0.3653999865055084},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35519999265670776},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C2992660569","wikidata":"https://www.wikidata.org/wiki/Q8068","display_name":"River flood","level":3,"score":0.32690000534057617},{"id":"https://openalex.org/C81299745","wikidata":"https://www.wikidata.org/wiki/Q334269","display_name":"Transfer function","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3140999972820282},{"id":"https://openalex.org/C115527620","wikidata":"https://www.wikidata.org/wiki/Q769909","display_name":"Nonlinear programming","level":3,"score":0.3077000081539154},{"id":"https://openalex.org/C155681218","wikidata":"https://www.wikidata.org/wiki/Q193110","display_name":"Floodplain","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C539955404","wikidata":"https://www.wikidata.org/wiki/Q1187968","display_name":"Flood control","level":3,"score":0.2906999886035919},{"id":"https://openalex.org/C76886044","wikidata":"https://www.wikidata.org/wiki/Q2883300","display_name":"Hydrology (agriculture)","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2644999921321869},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25690001249313354},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.25119999051094055},{"id":"https://openalex.org/C2987722363","wikidata":"https://www.wikidata.org/wiki/Q192704","display_name":"Transfer efficiency","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21203/rs.3.rs-11382325/v1","doi":"https://doi.org/10.21203/rs.3.rs-11382325/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11382325/v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.21203/rs.3.rs-11382325/v1","doi":"https://doi.org/10.21203/rs.3.rs-11382325/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11382325/v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Physics-informed":[1],"neural":[2,19,111],"networks":[3],"(PINNs)":[4],"have":[5],"shown":[6],"considerable":[7],"potential":[8],"for":[9,91,131,235],"solving":[10],"hydraulic":[11,51,55],"problems":[12],"by":[13,136],"integrating":[14],"governing":[15],"physical":[16],"laws":[17],"into":[18],"network":[20,112],"optimization.":[21,43],"However,":[22],"their":[23],"application":[24],"to":[25,127,214],"real-world":[26,151,231],"river":[27,93,152,239],"flood":[28,97,119,133,161,200,240,244],"remains":[29],"challenging":[30],"because":[31],"of":[32,89,233],"the":[33,83,129,206,230],"high":[34],"computational":[35,70],"cost":[36],"associated":[37],"with":[38,154,170],"nonlinear":[39],"and":[40,68,86,158,181,194,198,218,237],"non-convex":[41],"PINN":[42,102,130],"Conventional":[44],"PINNs":[45,90,174,234],"are":[46,124],"generally":[47],"initialized":[48,173],"without":[49],"task-specific":[50],"knowledge,":[52],"each":[53],"new":[54],"scenario":[56],"requires":[57],"optimization":[58,137,219],"from":[59],"an":[60,210],"uninformed":[61],"initial":[62],"state,":[63],"resulting":[64],"in":[65,107],"repeated":[66],"training":[67,87],"substantial":[69],"expense.":[71],"This":[72],"study":[73],"proposes":[74],"a":[75,109,117,139,150],"transfer":[76,100,225],"learning":[77,226],"method":[78],"that":[79,205,224],"can":[80],"significantly":[81,228],"improve":[82],"prediction":[84,216],"accuracy":[85,217],"efficiency":[88],"complex":[92,155,199],"floods":[94],"under":[95,190,195,242],"varying":[96,243],"events.":[98,245],"A":[99],"learning-enhanced":[101],"(TL-PINN)":[103],"framework":[104,146],"is":[105,113,147,168],"developed,":[106],"which":[108],"data-driven":[110],"first":[114],"trained":[115],"on":[116,149],"source":[118],"event.":[120],"The":[121,144,202],"optimized":[122],"parameters":[123,208],"then":[125],"transferred":[126,207],"initialize":[128],"target":[132],"events,":[134],"followed":[135],"using":[138,175],"composite":[140],"physics-informed":[141],"loss":[142],"function.":[143],"proposed":[145],"evaluated":[148],"reach":[153],"channel":[156],"geometry":[157],"highly":[159],"unsteady":[160],"processes":[162],"through":[163],"three":[164,171],"numerical":[165],"experiments.":[166],"TL-PINN":[167,185],"compared":[169],"conventionally":[172],"PyTorch":[176],"Default":[177],"Initialization,":[178],"Orthogonal":[179],"Initialization":[180],"Xavier":[182],"Normal":[183],"Initialization.":[184],"consistently":[186],"maintains":[187],"superior":[188],"performance":[189],"limited":[191],"labeled-data":[192],"conditions":[193],"more":[196],"severe":[197],"inflows.":[201],"results":[203],"indicate":[204],"provide":[209],"effective":[211],"initialization,":[212],"leading":[213],"improved":[215],"efficiency.":[220],"These":[221],"findings":[222],"demonstrate":[223],"might":[227],"enhance":[229],"applicability":[232],"efficient":[236],"accurate":[238],"simulations":[241]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-11T00:00:00"}
