{"id":"https://openalex.org/W4385484583","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191301","title":"Training Physics- Informed Neural Networks via Multi-Task Optimization for Traffic Density Prediction","display_name":"Training Physics- Informed Neural Networks via Multi-Task Optimization for Traffic Density Prediction","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385484583","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191301"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5103720716","display_name":"Bo Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Bo Wang","raw_affiliation_strings":["Swinburne University of Technology,Dept. of Computing Technologies,Melbourne,Australia","Dept. of Computing Technologies, Swinburne University of Technology, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Swinburne University of Technology,Dept. of Computing Technologies,Melbourne,Australia","institution_ids":["https://openalex.org/I57093077"]},{"raw_affiliation_string":"Dept. of Computing Technologies, Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006614329","display_name":"A. K. Qin","orcid":"https://orcid.org/0000-0001-6631-1651"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"A. K. Qin","raw_affiliation_strings":["Swinburne University of Technology,Dept. of Computing Technologies,Melbourne,Australia","Dept. of Computing Technologies, Swinburne University of Technology, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Swinburne University of Technology,Dept. of Computing Technologies,Melbourne,Australia","institution_ids":["https://openalex.org/I57093077"]},{"raw_affiliation_string":"Dept. of Computing Technologies, Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025844181","display_name":"Sajjad Shafiei","orcid":"https://orcid.org/0000-0002-0155-6866"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sajjad Shafiei","raw_affiliation_strings":["Swinburne University of Technology,Dept. of Computing Technologies,Melbourne,Australia","Dept. of Computing Technologies, Swinburne University of Technology, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Swinburne University of Technology,Dept. of Computing Technologies,Melbourne,Australia","institution_ids":["https://openalex.org/I57093077"]},{"raw_affiliation_string":"Dept. of Computing Technologies, Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063743712","display_name":"Hussein Dia","orcid":"https://orcid.org/0000-0001-8778-7296"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hussein Dia","raw_affiliation_strings":["Swinburne University of Technology,Dept. of Civil and Construction Engineering,Melbourne,Australia","Dept. of Civil and Construction Engineering, Swinburne University of Technology, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Swinburne University of Technology,Dept. of Civil and Construction Engineering,Melbourne,Australia","institution_ids":["https://openalex.org/I57093077"]},{"raw_affiliation_string":"Dept. of Civil and Construction Engineering, Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087297482","display_name":"Adriana\u2010Simona Mih\u0103i\u0163\u0103","orcid":"https://orcid.org/0000-0001-7670-5777"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Adriana-Simona Mihaita","raw_affiliation_strings":["Data Science Institute University of Technology Sydney,Sydney,Australia","Data Science Institute University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Data Science Institute University of Technology Sydney,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"Data Science Institute University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059128645","display_name":"Hanna Grzybowska","orcid":"https://orcid.org/0000-0003-2614-5964"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"funder","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hanna Grzybowska","raw_affiliation_strings":["Simulation Group, Data 61&#x007C;CSIRO,Sydney,Australia"],"affiliations":[{"raw_affiliation_string":"Simulation Group, Data 61&#x007C;CSIRO,Sydney,Australia","institution_ids":["https://openalex.org/I1292875679","https://openalex.org/I42894916"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5103720716"],"corresponding_institution_ids":["https://openalex.org/I57093077"],"apc_list":null,"apc_paid":null,"fwci":0.9891,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7350419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9950000047683716,"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":0.9950000047683716,"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/T10320","display_name":"Neural Networks and Applications","score":0.9663000106811523,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9549000263214111,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/task","display_name":"Task (project management)","score":0.695071280002594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6601482033729553},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6335468888282776},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6074332594871521},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5837973952293396},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5780109167098999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5125565528869629},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48188215494155884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10944098234176636},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10251486301422119}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.695071280002594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6601482033729553},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6335468888282776},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6074332594871521},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5837973952293396},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5780109167098999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5125565528869629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48188215494155884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10944098234176636},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10251486301422119},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W191859250","https://openalex.org/W1533861849","https://openalex.org/W1821462560","https://openalex.org/W1965900320","https://openalex.org/W2029465969","https://openalex.org/W2032137277","https://openalex.org/W2066671570","https://openalex.org/W2095797625","https://openalex.org/W2113145584","https://openalex.org/W2413527939","https://openalex.org/W2730438699","https://openalex.org/W2763433602","https://openalex.org/W2795982117","https://openalex.org/W2899283552","https://openalex.org/W2967912081","https://openalex.org/W2995435108","https://openalex.org/W3003922491","https://openalex.org/W3012417314","https://openalex.org/W3034368386","https://openalex.org/W3047001618","https://openalex.org/W3090337104","https://openalex.org/W3101378293","https://openalex.org/W3129051607","https://openalex.org/W3138154797","https://openalex.org/W3163993681","https://openalex.org/W3168972368","https://openalex.org/W3196004889","https://openalex.org/W3199139896","https://openalex.org/W4285109022","https://openalex.org/W4312771865","https://openalex.org/W6631943919","https://openalex.org/W6638523607","https://openalex.org/W6658819164","https://openalex.org/W6674344953","https://openalex.org/W6676544178","https://openalex.org/W6762287338"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W3162204513","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W2371138613","https://openalex.org/W100620283","https://openalex.org/W2495260952"],"abstract_inverted_index":{"Physics-informed":[0],"neural":[1,38],"networks":[2],"(PINN":[3],"s)":[4],"are":[5,136],"a":[6,21,44,94,118],"newly":[7],"emerging":[8],"research":[9],"frontier":[10],"in":[11,156,162,209],"machine":[12],"learning,":[13],"which":[14],"incorporate":[15],"certain":[16],"physical":[17,110],"laws":[18],"that":[19,199],"govern":[20],"given":[22,143],"data":[23,45],"set,":[24],"e.g.,":[25],"those":[26],"described":[27],"by":[28],"partial":[29],"differential":[30],"equations":[31],"(PDEs),":[32],"into":[33],"the":[34,37,50,54,58,61,65,70,75,80,84,100,103,125,142,147,170,174,179,187,191,212,217],"training":[35,88,91,121,202,216],"of":[36,79,87,102,106,172,215],"network":[39],"(NN)":[40],"based":[41,123],"on":[42,124],"such":[43],"set.":[46],"In":[47,113],"PINN":[48,120,188],"s,":[49],"NN":[51,71,81,108],"acts":[52,63],"as":[53,64],"solution":[55],"approximator":[56],"for":[57,189],"PDE":[59,62],"while":[60],"prior":[66],"knowledge":[67,149],"to":[68,74,99,160,168,185,205,211],"guide":[69],"training,":[72],"leading":[73],"desired":[76],"generalization":[77],"performance":[78,171,207],"when":[82],"facing":[83],"limited":[85],"availability":[86],"data.":[89],"However,":[90],"PINNs":[92],"is":[93,154],"non-trivial":[95],"task":[96,153],"largely":[97],"due":[98],"complexity":[101],"loss":[104],"composed":[105],"both":[107],"and":[109,138,182],"law":[111],"parts.":[112],"this":[114,131],"work,":[115],"we":[116],"propose":[117],"new":[119],"framework":[122,181,203],"multi-task":[126],"optimization":[127],"(MTO)":[128],"paradigm.":[129],"Under":[130],"framework,":[132],"multiple":[133],"auxiliary":[134],"tasks":[135],"created":[137],"solved":[139],"together":[140],"with":[141],"(main)":[144],"task,":[145],"where":[146],"useful":[148],"from":[150],"solving":[151,163,173],"one":[152],"transferred":[155],"an":[157],"adaptive":[158],"mode":[159],"assist":[161],"some":[164],"other":[165],"tasks,":[166],"aiming":[167],"uplift":[169],"main":[175],"task.":[176],"We":[177],"implement":[178],"proposed":[180,201],"apply":[183],"it":[184],"train":[186],"addressing":[190],"traffic":[192],"density":[193],"prediction":[194],"problem.":[195],"Experimental":[196],"results":[197],"demonstrate":[198],"our":[200],"leads":[204],"significant":[206],"improvement":[208],"comparison":[210],"traditional":[213],"way":[214],"PINN.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
