{"id":"https://openalex.org/W3123688691","doi":"https://doi.org/10.1109/tkde.2021.3112977","title":"Modeling Spatial Nonstationarity via Deformable Convolutions for Deep Traffic Flow Prediction","display_name":"Modeling Spatial Nonstationarity via Deformable Convolutions for Deep Traffic Flow Prediction","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3123688691","doi":"https://doi.org/10.1109/tkde.2021.3112977","mag":"3123688691"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3112977","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3112977","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2101.12010","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wei Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]},{"id":"https://openalex.org/I4210106808","display_name":"Guangzhou Institute of Advanced Technology","ror":"https://ror.org/01vcw4681","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210106808"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Zeng","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Guangzhou Branch, 53042 Guangzhou, Guangdong, China, 510070 (e-mail: wei.zeng@siat.ac.cn)"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Guangzhou Branch, 53042 Guangzhou, Guangdong, China, 510070 (e-mail: wei.zeng@siat.ac.cn)","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I4210106808"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chengqiao Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengqiao Lin","raw_affiliation_strings":["School of Informatics, Xiamen University, 12466 Xiamen, Fujian, China, (e-mail: linchengqiao@xmu.edu.cn)"],"affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, 12466 Xiamen, Fujian, China, (e-mail: linchengqiao@xmu.edu.cn)","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Liu","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 12381 Shenzhen, Guangdong, China, (e-mail: kang.liu@siat.ac.cn)"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 12381 Shenzhen, Guangdong, China, (e-mail: kang.liu@siat.ac.cn)","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Juncong Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juncong Lin","raw_affiliation_strings":["School of Informatics, Xiamen University, Xiamen, Fujian, China, (e-mail: jclin@xmu.edu.cn)"],"affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, Fujian, China, (e-mail: jclin@xmu.edu.cn)","institution_ids":["https://openalex.org/I191208505","https://openalex.org/I75867142"]}]},{"author_position":"last","author":{"id":null,"display_name":"Anthony K. H. Tung","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Anthony K. H. Tung","raw_affiliation_strings":["Department of Computer Science, National University of Singapore, Singapore, Singapore, Singapore, 148955 (e-mail: atung@comp.nus.edu.sg)"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National University of Singapore, Singapore, Singapore, Singapore, 148955 (e-mail: atung@comp.nus.edu.sg)","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210106808","https://openalex.org/I4210145761"],"apc_list":null,"apc_paid":null,"fwci":1.3353,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.77614216,"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":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9463000297546387,"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":0.9463000297546387,"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":0.02239999920129776,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.003100000089034438,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/raster-graphics","display_name":"Raster graphics","score":0.6269999742507935},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5835999846458435},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5733000040054321},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5508999824523926},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.522599995136261},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.400299996137619},{"id":"https://openalex.org/keywords/spatial-network","display_name":"Spatial network","score":0.3734000027179718}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.754800021648407},{"id":"https://openalex.org/C181844469","wikidata":"https://www.wikidata.org/wiki/Q182270","display_name":"Raster graphics","level":2,"score":0.6269999742507935},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5835999846458435},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5733000040054321},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5508999824523926},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.522599995136261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4909000098705292},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.400299996137619},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38429999351501465},{"id":"https://openalex.org/C53471067","wikidata":"https://www.wikidata.org/wiki/Q7574076","display_name":"Spatial network","level":2,"score":0.3734000027179718},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3700999915599823},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3553999960422516},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C158709400","wikidata":"https://www.wikidata.org/wiki/Q3578586","display_name":"Spatial ecology","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C2692088","wikidata":"https://www.wikidata.org/wiki/Q182270","display_name":"Raster data","level":3,"score":0.2915000021457672},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2856999933719635},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C203332170","wikidata":"https://www.wikidata.org/wiki/Q6334079","display_name":"Multivariate interpolation","level":3,"score":0.2623000144958496},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2574999928474426},{"id":"https://openalex.org/C203689450","wikidata":"https://www.wikidata.org/wiki/Q2302053","display_name":"Spatial database","level":3,"score":0.2524999976158142},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2021.3112977","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3112977","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2101.12010","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.12010","pdf_url":"https://arxiv.org/pdf/2101.12010","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2101.12010","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.12010","pdf_url":"https://arxiv.org/pdf/2101.12010","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1604913257","display_name":null,"funder_award_id":"61802388","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1973749534","https://openalex.org/W1990444226","https://openalex.org/W2016210396","https://openalex.org/W2024558842","https://openalex.org/W2028226037","https://openalex.org/W2030861104","https://openalex.org/W2036785686","https://openalex.org/W2047120335","https://openalex.org/W2052611179","https://openalex.org/W2066377449","https://openalex.org/W2069929199","https://openalex.org/W2087443150","https://openalex.org/W2111991989","https://openalex.org/W2118898434","https://openalex.org/W2131819535","https://openalex.org/W2136331893","https://openalex.org/W2145039203","https://openalex.org/W2150010190","https://openalex.org/W2153207204","https://openalex.org/W2165991108","https://openalex.org/W2194775991","https://openalex.org/W2342045095","https://openalex.org/W2399767476","https://openalex.org/W2412782625","https://openalex.org/W2528639018","https://openalex.org/W2529026485","https://openalex.org/W2532536081","https://openalex.org/W2543927648","https://openalex.org/W2576554443","https://openalex.org/W2592939477","https://openalex.org/W2601564443","https://openalex.org/W2614121823","https://openalex.org/W2785362665","https://openalex.org/W2788134583","https://openalex.org/W2901504064","https://openalex.org/W2903871660","https://openalex.org/W2904813135","https://openalex.org/W2910892140","https://openalex.org/W2922146383","https://openalex.org/W2945622688","https://openalex.org/W2963076818","https://openalex.org/W2997563066","https://openalex.org/W2997848713","https://openalex.org/W3021253665","https://openalex.org/W3024861527","https://openalex.org/W3027983943","https://openalex.org/W3034347085","https://openalex.org/W3046252510","https://openalex.org/W3083569822","https://openalex.org/W3090457543","https://openalex.org/W3093457167","https://openalex.org/W3128199307","https://openalex.org/W6689637345","https://openalex.org/W6739696289"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"are":[3],"being":[4],"increasingly":[5],"used":[6],"for":[7,141],"short-term":[8],"traffic":[9,57,108,121,132,148,196],"flow":[10,197],"prediction,":[11],"which":[12],"can":[13,95],"be":[14],"generally":[15],"categorized":[16],"as":[17],"CNNs":[18,21,157],"or":[19,127,167],"GNNs.":[20],"typically":[22],"partition":[23,163,190],"an":[24],"underlying":[25],"territory":[26],"into":[27],"grid-like":[28],"spatial":[29,37,70,82,99,102,162,183],"units,":[30],"and":[31,104,155,161,185,192],"employ":[32],"standard":[33,43,159],"convolutions":[34,44],"to":[35,76,111,118,124,136],"learn":[36],"dependence":[38],"among":[39],"the":[40,52,61,69,78,172,177,187],"units.":[41],"However,":[42],"with":[45,73,114],"fixed":[46],"geometric":[47],"structures":[48],"cannot":[49],"fully":[50],"model":[51,97],"nonstationary":[53],"characteristics":[54],"of":[55,81,107,179,189],"local":[56,101],"flows.":[58,109],"To":[59],"overcome":[60],"deficiency,":[62],"we":[63,116],"introduce":[64],"deformable":[65,88],"convolution":[66],"that":[67,94,151],"augments":[68],"sampling":[71],"locations":[72],"additional":[74],"offsets,":[75],"enhance":[77],"modeling":[79],"capability":[80],"nonstationarity.":[83],"We":[84,174],"design":[85],"a":[86],"deep":[87,195],"convolutional":[89],"residual":[90],"network,":[91],"namely":[92],"DeFlow-Net,":[93],"effectively":[96],"global":[98],"dependence,":[100],"nonstationarity,":[103],"temporal":[105],"periodicity":[106],"Furthermore,":[110],"better":[112],"fit":[113],"convolutions,":[115,160],"suggest":[117],"first":[119],"aggregate":[120],"flows":[122,149],"according":[123],"pre-conceived":[125,165],"regions":[126,129,166,169],"self-organized":[128,168],"based":[130],"on":[131,146,194],"flows,":[133],"then":[134],"dispose":[135],"sequentially":[137],"organized":[138],"raster":[139],"images":[140],"network":[142],"input.":[143],"Extensive":[144],"experiments":[145],"real-world":[147],"demonstrate":[150,176],"DeFlow-Net":[152,180],"outperforms":[153],"GNNs":[154],"existing":[156],"using":[158],"by":[164],"further":[170],"enhances":[171],"performance.":[173],"also":[175],"advantage":[178],"in":[181],"maintaining":[182],"autocorrelation,":[184],"reveal":[186],"impacts":[188],"shapes":[191],"scales":[193],"prediction.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2021-02-01T00:00:00"}
