{"id":"https://openalex.org/W7225449341","doi":"https://doi.org/10.1007/s44163-026-02714-x","title":"Cross-regional hydro-meteorological cascade propagation modeling and emergency response optimization using temporal fusion transformer and spatio-temporal GNN","display_name":"Cross-regional hydro-meteorological cascade propagation modeling and emergency response optimization using temporal fusion transformer and spatio-temporal GNN","publication_year":2026,"publication_date":"2026-11-07","ids":{"openalex":"https://openalex.org/W7225449341","doi":"https://doi.org/10.1007/s44163-026-02714-x"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-026-02714-x","doi":"https://doi.org/10.1007/s44163-026-02714-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-02714-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-02714-x.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","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://link.springer.com/content/pdf/10.1007/s44163-026-02714-x.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069519808","display_name":"Chen Longkai","orcid":"https://orcid.org/0009-0000-4498-2956","observed_orcids":["https://orcid.org/0009-0000-4498-2956"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Longkai Chen","raw_affiliation_strings":["Research Department of Secretariat, Emergency Governance Society of Shenzhen, Shenzhen, 518000, China"],"raw_orcid":"https://orcid.org/0009-0000-4498-2956","affiliations":[{"raw_affiliation_string":"Research Department of Secretariat, Emergency Governance Society of Shenzhen, Shenzhen, 518000, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5069519808"],"corresponding_institution_ids":[],"apc_list":{"value":1590,"currency":"USD","value_usd":1590},"apc_paid":{"value":1590,"currency":"USD","value_usd":1590},"fwci":0.0,"has_fulltext":true,"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":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10747","display_name":"Disaster Management and Resilience","score":0.26269999146461487,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T10747","display_name":"Disaster Management and Resilience","score":0.26269999146461487,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T14250","display_name":"Energy and Environmental Systems","score":0.17749999463558197,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.14380000531673431,"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/hydrometeorological-disasters","display_name":"hydrometeorological disasters","score":0.8360000252723694},{"id":"https://openalex.org/keywords/temporal-fusion-transformer","display_name":"Temporal Fusion Transformer","score":0.8360000252723694},{"id":"https://openalex.org/keywords/spatiotemporal-graph-neural-networks","display_name":"spatio-temporal graph neural networks","score":0.9490000009536743},{"id":"https://openalex.org/keywords/flood-risk-prediction","display_name":"flood risk prediction","score":0.5699999928474426},{"id":"https://openalex.org/keywords/integer-programming","display_name":"integer programming","score":0.9039999842643738},{"id":"https://openalex.org/keywords/quantile-regression","display_name":"quantile regression","score":0.7789999842643738},{"id":"https://openalex.org/keywords/decision-support","display_name":"decision support","score":0.4440000057220459}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7107999920845032},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5827000141143799},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.43479999899864197},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.3727000057697296},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.3619999885559082},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3416999876499176},{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.3301999866962433},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C2777632111","wikidata":"https://www.wikidata.org/wiki/Q1937518","display_name":"Reservation","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2775999903678894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2775000035762787},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2752000093460083},{"id":"https://openalex.org/C62555980","wikidata":"https://www.wikidata.org/wiki/Q1460420","display_name":"Emergency management","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2583000063896179},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-026-02714-x","doi":"https://doi.org/10.1007/s44163-026-02714-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-02714-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-02714-x.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8da034746d7b4e7683a25c5fa22c264b","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/8da034746d7b4e7683a25c5fa22c264b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 6, Iss 1 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-026-02714-x","doi":"https://doi.org/10.1007/s44163-026-02714-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-02714-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-026-02714-x.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1","oarl"],"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.7207000255584717,"id":"https://metadata.un.org/sdg/9"},{"display_name":"Climate action","score":0.5351999998092651,"id":"https://metadata.un.org/sdg/13"},{"display_name":"Sustainable cities and communities","score":0.5142999887466431,"id":"https://metadata.un.org/sdg/11"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225449341.pdf","grobid_xml":"https://content.openalex.org/works/W7225449341.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W2030490025","https://openalex.org/W2076199148","https://openalex.org/W2519887557","https://openalex.org/W2768008502","https://openalex.org/W2965341826","https://openalex.org/W2996331899","https://openalex.org/W3038981236","https://openalex.org/W4223943844","https://openalex.org/W4226485774","https://openalex.org/W4282935706","https://openalex.org/W4298325715","https://openalex.org/W4316037472","https://openalex.org/W4323923239","https://openalex.org/W4367171858","https://openalex.org/W4367186660","https://openalex.org/W4372329045","https://openalex.org/W4382137225","https://openalex.org/W4385651631","https://openalex.org/W4387867530","https://openalex.org/W4388076698","https://openalex.org/W4389617220","https://openalex.org/W4390055508","https://openalex.org/W4390266907","https://openalex.org/W4390673747","https://openalex.org/W4391547546","https://openalex.org/W4391574361","https://openalex.org/W4392634046","https://openalex.org/W4392662539","https://openalex.org/W4394944121","https://openalex.org/W4396674469","https://openalex.org/W4399990193","https://openalex.org/W4401190470","https://openalex.org/W4402442455","https://openalex.org/W4402542611","https://openalex.org/W4403953208","https://openalex.org/W4406025379","https://openalex.org/W4406592749","https://openalex.org/W4408095418","https://openalex.org/W4411675756","https://openalex.org/W4412154851","https://openalex.org/W4412355938","https://openalex.org/W4413029275","https://openalex.org/W4414164109","https://openalex.org/W4414472556","https://openalex.org/W7124742539","https://openalex.org/W7155102495"],"related_works":["https://openalex.org/W4416181777","https://openalex.org/W7124440363","https://openalex.org/W7160825986","https://openalex.org/W7204456292","https://openalex.org/W4388908554","https://openalex.org/W7213632916","https://openalex.org/W7108473531","https://openalex.org/W7196933796","https://openalex.org/W7225443539","https://openalex.org/W7131167637"],"abstract_inverted_index":{"Cross-regional":[0],"hydro-meteorological":[1],"disasters":[2],"(e.g.,":[3],"floods,":[4],"heavy":[5],"rainfall-triggered":[6],"cascades)":[7],"often":[8],"trigger":[9],"cascading":[10,191],"propagation":[11,192],"effects":[12],"with":[13,255],"strong":[14],"spatiotemporal":[15],"dependencies":[16,85],"due":[17],"to":[18,41,168],"geographical":[19,111],"proximity,":[20],"infrastructure":[21],"interconnectivity,":[22],"and":[23,61,92,114,127,129,142,152,207,218,243,246],"socioeconomic":[24],"coupling.":[25],"Existing":[26],"emergency":[27,253],"response":[28,221],"systems":[29],"lack":[30],"high-precision,":[31],"interpretable":[32],"predictive":[33],"capabilities":[34],"for":[35,165,251],"such":[36],"dynamic":[37,104],"transmission":[38],"processes,":[39],"leading":[40],"delayed":[42],"coordinated":[43],"responses.":[44],"To":[45],"address":[46],"this":[47,49,181],"issue,":[48],"paper":[50],"constructs":[51,101],"a":[52,102,109,135,174,199,231,237,260],"joint":[53],"modeling":[54],"framework":[55,66],"integrating":[56],"Temporal":[57],"Fusion":[58],"Transformer":[59],"(TFT)":[60],"Spatio-Temporal":[62],"GNN":[63],"(ST-GNN).":[64],"This":[65],"inputs":[67,164],"multi-source":[68],"covariates":[69],"from":[70],"each":[71,120,146],"region":[72],"into":[73],"the":[74,190],"variable":[75],"selection":[76],"network":[77,216],"of":[78,187,194,202,211,223],"TFT.":[79],"After":[80],"gated":[81],"residual":[82],"processing,":[83],"long-term":[84],"are":[86,125,132,159],"jointly":[87],"modeled":[88],"using":[89],"multi-head":[90],"self-attention":[91],"causal":[93],"convolution,":[94],"outputting":[95],"regional":[96],"temporal":[97],"states.":[98],"Simultaneously,":[99],"ST-GNN":[100],"task-adapted":[103],"adjacency":[105,112],"graph":[106],"based":[107],"on":[108,259],"predefined":[110],"matrix":[113],"adaptively":[115],"learned":[116],"edge":[117],"weights.":[118],"At":[119],"time":[121,222],"step,":[122,148],"neighbor":[123],"nodes":[124],"aggregated":[126],"embedded,":[128],"node":[130,215],"representations":[131],"updated":[133],"via":[134],"time-gated":[136],"mechanism.":[137],"Both":[138],"approaches":[139],"align":[140],"timestamps":[141],"concatenate":[143],"features":[144],"in":[145,189,240],"prediction":[147,153,193,241],"generating":[149],"risk":[150],"intensity":[151],"intervals":[154],"through":[155],"quantile":[156],"regression.":[157],"These":[158],"then":[160],"used":[161],"as":[162],"constraint":[163],"integer":[166],"programming":[167],"solve":[169],"resource":[170],"scheduling":[171],"schemes,":[172],"forming":[173],"closed-loop":[175],"decision.":[176],"Comparative":[177],"experiments":[178],"show":[179],"that":[180],"method":[182],"achieves":[183,236],"an":[184,208,219],"average":[185,220],"RMSE":[186],"0.071":[188],"highly":[195],"disturbed":[196],"disaster":[197],"distributions,":[198],"recall":[200],"rate":[201],"0.97,":[203],"precision":[204],"at":[205],"0.95,":[206],"F1":[209],"score":[210],"0.96":[212],"under":[213,227],"extreme":[214],"density,":[217],"only":[224],"5.6":[225],"s":[226],"500":[228],"nodes.":[229],"As":[230],"proof-of-concept":[232],"simulation":[233],"framework,":[234],"it":[235],"synergistic":[238],"improvement":[239],"accuracy":[242],"decision-making":[244],"efficiency,":[245],"provides":[247],"quantifiable":[248],"decision":[249],"support":[250],"cross-regional":[252],"response,":[254],"retrospective":[256],"case":[257],"validation":[258],"documented":[261],"historical":[262],"event.":[263]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-08T00:00:00"}