{"id":"https://openalex.org/W7225834513","doi":"https://doi.org/10.3390/math14224135","title":"Residual Diffusion-Enhanced Spatio-Temporal Network for Human Mobility Forecasting in Disaster Scenarios","display_name":"Residual Diffusion-Enhanced Spatio-Temporal Network for Human Mobility Forecasting in Disaster Scenarios","publication_year":2026,"publication_date":"2026-11-11","ids":{"openalex":"https://openalex.org/W7225834513","doi":"https://doi.org/10.3390/math14224135"},"language":"en","primary_location":{"id":"doi:10.3390/math14224135","doi":"https://doi.org/10.3390/math14224135","is_oa":true,"landing_page_url":"https://doi.org/10.3390/math14224135","pdf_url":null,"source":{"id":"https://openalex.org/S4210192031","display_name":"Mathematics","issn_l":"2227-7390","issn":["2227-7390"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/math14224135","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121963325","display_name":"Xing Gao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Gao","raw_affiliation_strings":["College of Applied Science, Shenzhen University, Shenzhen 518000, China","School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Applied Science, Shenzhen University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357865","display_name":"Meng Chen","orcid":"https://orcid.org/0000-0003-0774-3133","observed_orcids":["https://orcid.org/0000-0003-0774-3133"]},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Chen","raw_affiliation_strings":["School of Software, Shandong University, Jinan 250100, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan 250100, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161427492","display_name":"Nan Yin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Nan Yin","raw_affiliation_strings":["Department of Computer Science and Technology, Hong Kong University of Science and Technology, Hong Kong 999077, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Hong Kong University of Science and Technology, Hong Kong 999077, China","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032508900","display_name":"Jingyan Jiang","orcid":"https://orcid.org/0000-0003-4897-2645","observed_orcids":["https://orcid.org/0000-0003-4897-2645"]},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyan Jiang","raw_affiliation_strings":["School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China"],"raw_orcid":"https://orcid.org/0000-0003-4897-2645","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083350101","display_name":"Xiuqiang He","orcid":"https://orcid.org/0000-0002-4115-8205","observed_orcids":["https://orcid.org/0000-0002-4115-8205"]},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuqiang He","raw_affiliation_strings":["School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160575245","display_name":"Bowen Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075800064","display_name":"Hu Huang","orcid":"https://orcid.org/0009-0005-9674-258X","observed_orcids":["https://orcid.org/0009-0005-9674-258X"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hu Huang","raw_affiliation_strings":["School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018994926","display_name":"Genan Dai","orcid":"https://orcid.org/0000-0003-2583-0433","observed_orcids":["https://orcid.org/0000-0003-2583-0433"]},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Genan Dai","raw_affiliation_strings":["School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210152380"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018994926","https://openalex.org/A5075800064"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210152380"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"22","first_page":"4135","last_page":"4135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.5351999998092651,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.5351999998092651,"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"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.45339998602867126,"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"}},{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.0020000000949949026,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8640000224113464},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6414999961853027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6355000138282776},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.5670999884605408},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4966999888420105},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4823000133037567},{"id":"https://openalex.org/C191485582","wikidata":"https://www.wikidata.org/wiki/Q6887309","display_name":"Mobility model","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3781999945640564},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35190001130104065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.334199994802475},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.29510000348091125},{"id":"https://openalex.org/C63002673","wikidata":"https://www.wikidata.org/wiki/Q2260590","display_name":"Scoring rule","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C49261128","wikidata":"https://www.wikidata.org/wiki/Q1132455","display_name":"Hazard","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.271699994802475},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/math14224135","doi":"https://doi.org/10.3390/math14224135","is_oa":true,"landing_page_url":"https://doi.org/10.3390/math14224135","pdf_url":null,"source":{"id":"https://openalex.org/S4210192031","display_name":"Mathematics","issn_l":"2227-7390","issn":["2227-7390"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/math14224135","doi":"https://doi.org/10.3390/math14224135","is_oa":true,"landing_page_url":"https://doi.org/10.3390/math14224135","pdf_url":null,"source":{"id":"https://openalex.org/S4210192031","display_name":"Mathematics","issn_l":"2227-7390","issn":["2227-7390"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mathematics","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1711412747","https://openalex.org/W1975372198","https://openalex.org/W2069929199","https://openalex.org/W2073795924","https://openalex.org/W2119061727","https://openalex.org/W2528639018","https://openalex.org/W2756203131","https://openalex.org/W2963341956","https://openalex.org/W2965341826","https://openalex.org/W2997848713","https://openalex.org/W3011157584","https://openalex.org/W3080252065","https://openalex.org/W3080253043","https://openalex.org/W3107893393","https://openalex.org/W3138340468","https://openalex.org/W3196222640","https://openalex.org/W4205320585","https://openalex.org/W4312703862","https://openalex.org/W4381786018","https://openalex.org/W4382239616","https://openalex.org/W4382466628","https://openalex.org/W4384789416","https://openalex.org/W4385270450","https://openalex.org/W4387717460","https://openalex.org/W4387846219","https://openalex.org/W4388936714","https://openalex.org/W4390100390","https://openalex.org/W4390100419","https://openalex.org/W4401024533","https://openalex.org/W4402754191","https://openalex.org/W4405429237","https://openalex.org/W4407097607","https://openalex.org/W4407158202","https://openalex.org/W4407574873","https://openalex.org/W4408352200","https://openalex.org/W4408803960","https://openalex.org/W4409245874","https://openalex.org/W4410640244","https://openalex.org/W4414360478","https://openalex.org/W4414538315","https://openalex.org/W4415746026","https://openalex.org/W4416252172","https://openalex.org/W7124441788","https://openalex.org/W7156117011","https://openalex.org/W7162659610","https://openalex.org/W7163580729","https://openalex.org/W7164944492","https://openalex.org/W7171998433","https://openalex.org/W7196956625","https://openalex.org/W7206156585"],"related_works":[],"abstract_inverted_index":{"Forecasting":[0],"human":[1],"mobility":[2,23,50,66,95,154],"during":[3],"disasters":[4,14],"is":[5,194],"essential":[6],"for":[7,174],"emergency":[8],"response":[9],"but":[10,31,43],"remains":[11],"challenging":[12],"because":[13],"cause":[15],"abrupt,":[16],"uncertain,":[17],"and":[18,72,84,102,124,161,165],"context-dependent":[19],"deviations":[20],"from":[21,129],"regular":[22,70],"patterns.":[24],"Deterministic":[25],"models":[26,39,110],"capture":[27],"dominant":[28],"spatio-temporal":[29,62],"patterns":[30],"tend":[32],"to":[33,169,196],"underrepresent":[34],"these":[35,54],"deviations,":[36],"whereas":[37],"diffusion-based":[38],"characterize":[40],"predictive":[41],"uncertainty":[42],"may":[44],"generate":[45],"forecasts":[46],"inconsistent":[47],"with":[48,198,207],"historical":[49,121],"dynamics.":[51],"To":[52],"overcome":[53],"limitations,":[55],"we":[56],"propose":[57],"ResDiffNet,":[58],"a":[59,69,73,79,87,98,103,115,138,220],"residual":[60,74,104,135,222],"diffusion-enhanced":[61],"network":[63],"that":[64,157],"decomposes":[65],"dynamics":[67],"into":[68],"trend":[71,96,122],"deviation.":[75],"This":[76],"decomposition":[77],"enables":[78],"principled":[80],"integration":[81],"of":[82,145],"deterministic":[83,88,209],"diffusion":[85,106,117,147],"modeling:":[86],"base":[89],"predictor":[90],"first":[91],"learns":[92],"the":[93,132,142,170,179,184],"stable":[94],"using":[97],"hypergraph":[99],"convolutional":[100],"network,":[101],"conditional":[105,116],"module":[107],"(RCDM)":[108],"subsequently":[109],"disaster-induced":[111],"stochastic":[112],"residuals":[113],"through":[114],"process.":[118],"Guided":[119],"by":[120,163],"signals":[123],"disaster-related":[125,153],"semantic":[126],"information":[127],"extracted":[128],"social":[130],"media,":[131],"RCDM":[133,206],"refines":[134],"predictions":[136],"in":[137],"context-aware":[139],"manner,":[140],"mitigating":[141],"excessive":[143],"randomness":[144],"standard":[146],"models.":[148],"Experiments":[149],"on":[150],"two":[151],"real-world":[152],"datasets":[155],"show":[156],"ResDiffNet":[158],"reduces":[159],"RMSE":[160],"MAE":[162],"4.5\u20137.0%":[164],"5.2\u20139.0%,":[166],"respectively,":[167],"relative":[168],"strongest":[171],"competing":[172],"baseline":[173],"each":[175],"task":[176],"while":[177],"achieving":[178],"lowest":[180],"mean":[181],"CRPS":[182,192],"among":[183],"evaluated":[185],"probabilistic":[186],"methods.":[187],"On":[188],"Storm-New":[189],"York":[190],"(Outflow),":[191],"performance":[193],"comparable":[195],"CoST,":[197],"no":[199],"statistically":[200],"significant":[201],"advantage":[202],"established.":[203],"Moreover,":[204],"integrating":[205],"four":[208],"predictors":[210],"consistently":[211],"improves":[212],"their":[213],"forecasting":[214],"accuracy,":[215],"supporting":[216],"its":[217],"use":[218],"as":[219],"plug-and-play":[221],"refinement":[223],"module.":[224]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-11-12T00:00:00"}
