{"id":"https://openalex.org/W7136804478","doi":"https://doi.org/10.1109/itsc60802.2025.11423113","title":"Adaptive Fusion of Decomposed Traffic Components: A Heterogenized Spatio-Temporal Attention for Traffic Forecasting","display_name":"Adaptive Fusion of Decomposed Traffic Components: A Heterogenized Spatio-Temporal Attention for Traffic Forecasting","publication_year":2025,"publication_date":"2025-11-18","ids":{"openalex":"https://openalex.org/W7136804478","doi":"https://doi.org/10.1109/itsc60802.2025.11423113"},"language":null,"primary_location":{"id":"doi:10.1109/itsc60802.2025.11423113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","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/A5039405717","display_name":"Tianhao Li","orcid":"https://orcid.org/0000-0003-3093-0447"},"institutions":[{"id":"https://openalex.org/I4210086892","display_name":"Education University of Hong Kong","ror":"https://ror.org/000t0f062","country_code":"HK","type":"education","lineage":["https://openalex.org/I4210086892"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Tianhao Li","raw_affiliation_strings":["The University of Hong Kong,Department of Urban Planning and Design,Hong Kong SAR,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Urban Planning and Design,Hong Kong SAR,China","institution_ids":["https://openalex.org/I4210086892","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129554276","display_name":"Zhan Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210086892","display_name":"Education University of Hong Kong","ror":"https://ror.org/000t0f062","country_code":"HK","type":"education","lineage":["https://openalex.org/I4210086892"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhan Zhao","raw_affiliation_strings":["The University of Hong Kong,Department of Urban Planning and Design,Hong Kong SAR,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Urban Planning and Design,Hong Kong SAR,China","institution_ids":["https://openalex.org/I4210086892","https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035743938","display_name":"Xintian Liu","orcid":"https://orcid.org/0000-0002-3395-9176"},"institutions":[{"id":"https://openalex.org/I4210086892","display_name":"Education University of Hong Kong","ror":"https://ror.org/000t0f062","country_code":"HK","type":"education","lineage":["https://openalex.org/I4210086892"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xintian Liu","raw_affiliation_strings":["The University of Hong Kong,Department of Urban Planning and Design,Hong Kong SAR,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Urban Planning and Design,Hong Kong SAR,China","institution_ids":["https://openalex.org/I4210086892","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5039405717"],"corresponding_institution_ids":["https://openalex.org/I4210086892","https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71696545,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1079","last_page":"1083"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9769999980926514,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9769999980926514,"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"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.005100000184029341,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4300999939441681},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.3968999981880188},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3434000015258789},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.2784000039100647}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.548799991607666},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4300999939441681},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4034000039100647},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.36500000953674316},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3172999918460846},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2921999990940094},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2784000039100647},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.271699994802475}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc60802.2025.11423113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1973943669","https://openalex.org/W1975362087","https://openalex.org/W2074812030","https://openalex.org/W2299288249","https://openalex.org/W2345702419","https://openalex.org/W2572939427","https://openalex.org/W2756203131","https://openalex.org/W2969210779","https://openalex.org/W3035184251","https://openalex.org/W3043505188","https://openalex.org/W3170140111","https://openalex.org/W3175924508","https://openalex.org/W3177318507","https://openalex.org/W4385270240"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"traffic":[1,14,34,40,59,123],"flow":[2,35,140],"forecasting":[3,36],"remains":[4],"challenging":[5],"due":[6],"to":[7,42,57],"the":[8],"heterogeneous":[9],"spatiotemporal":[10,83],"patterns":[11],"and":[12,30,53,68,78,91,100,135,142],"varying":[13,139],"components.":[15],"To":[16],"address":[17],"this,":[18],"we":[19],"propose":[20],"DCST":[21,24,95,127],"Fnet":[22,96,128],"(where":[23],"F":[25],"denotes":[26],"decomposition,":[27],"componential-spatial-temporal":[28],"attention,":[29],"fusion),":[31],"a":[32,50,81],"novel":[33],"framework":[37],"that":[38,126],"decomposes":[39],"data":[41],"enhance":[43],"predictive":[44],"accuracy.":[45],"The":[46],"model":[47],"first":[48],"leverages":[49],"vehicle-attribute":[51],"classifier":[52],"Discrete":[54],"Wavelet":[55],"Transform":[56],"split":[58],"time":[60],"series":[61],"into":[62,117],"components":[63],"representing":[64],"distinct":[65],"temporal":[66],"dynamics":[67],"behavioral":[69],"patterns.":[70],"Each":[71],"component":[72],"is":[73],"enriched":[74],"with":[75,111],"cross-component":[76],"information":[77],"processed":[79],"via":[80],"multi-channel":[82],"encoder.":[84],"By":[85],"integrating":[86],"both":[87,98,133],"dynamic":[88],"local":[89,99],"neighborhoods":[90],"globally":[92],"representative":[93],"nodes,":[94],"enables":[97],"global":[101],"attention-based":[102],"message":[103],"passing":[104],"among":[105],"nodes.":[106],"An":[107],"adaptive":[108],"fusion":[109],"module":[110],"multi-level":[112],"supervision":[113],"integrates":[114],"component-wise":[115],"predictions":[116],"final":[118],"forecasts.":[119],"Experiments":[120],"on":[121],"real-world":[122],"datasets":[124],"show":[125],"consistently":[129],"outperforms":[130],"baselines":[131],"in":[132],"accuracy":[134],"robustness,":[136],"particularly":[137],"under":[138],"intensities":[141],"prediction":[143],"horizons.":[144]},"counts_by_year":[],"updated_date":"2026-03-18T06:27:02.140700","created_date":"2026-03-17T00:00:00"}