{"id":"https://openalex.org/W2903211386","doi":"https://doi.org/10.1109/icpr.2018.8546257","title":"Local and Global Bayesian Network based Model for Flood Prediction","display_name":"Local and Global Bayesian Network based Model for Flood Prediction","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2903211386","doi":"https://doi.org/10.1109/icpr.2018.8546257","mag":"2903211386"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8546257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546257","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5053703016","display_name":"Yirui Wu","orcid":"https://orcid.org/0000-0003-3022-3718"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yirui Wu","raw_affiliation_strings":["College of Computer and Information, Hohai University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101717668","display_name":"Weigang Xu","orcid":"https://orcid.org/0000-0001-6070-1130"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weigang Xu","raw_affiliation_strings":["College of Computer and Information, Hohai University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101844109","display_name":"Jun Feng","orcid":"https://orcid.org/0000-0002-2627-5403"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Feng","raw_affiliation_strings":["College of Computer and Information, Hohai University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025871978","display_name":"Palaiahnakote Shivakumara","orcid":"https://orcid.org/0000-0001-9026-4613"},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Shivakumara Palaiahnakote","raw_affiliation_strings":["Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia","institution_ids":["https://openalex.org/I33849332"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061696740","display_name":"Tong L\u00fc","orcid":"https://orcid.org/0000-0002-7051-5347"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Lu","raw_affiliation_strings":["National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5053703016"],"corresponding_institution_ids":["https://openalex.org/I163340411"],"apc_list":null,"apc_paid":null,"fwci":1.709,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.8377313,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"225","last_page":"230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10330","display_name":"Hydrology and Watershed Management Studies","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7319082021713257},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.7090604305267334},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6974931955337524},{"id":"https://openalex.org/keywords/flood-myth","display_name":"Flood myth","score":0.5317527055740356},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48957547545433044},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4695988893508911},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4434361457824707},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4167741537094116},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11117267608642578}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7319082021713257},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.7090604305267334},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6974931955337524},{"id":"https://openalex.org/C74256435","wikidata":"https://www.wikidata.org/wiki/Q134052","display_name":"Flood myth","level":2,"score":0.5317527055740356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48957547545433044},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4695988893508911},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4434361457824707},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4167741537094116},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11117267608642578},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8546257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546257","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W156907250","https://openalex.org/W1511608140","https://openalex.org/W1672654364","https://openalex.org/W1817561967","https://openalex.org/W1863684228","https://openalex.org/W1972770267","https://openalex.org/W1990456124","https://openalex.org/W2014325697","https://openalex.org/W2018503939","https://openalex.org/W2074770406","https://openalex.org/W2100085182","https://openalex.org/W2143956628","https://openalex.org/W2155090659","https://openalex.org/W2160804315","https://openalex.org/W2160944830","https://openalex.org/W2181125631","https://openalex.org/W2302101267","https://openalex.org/W2623181128","https://openalex.org/W2724686580","https://openalex.org/W2783814294","https://openalex.org/W2786796754","https://openalex.org/W2963037989","https://openalex.org/W6606308608"],"related_works":["https://openalex.org/W2770593030","https://openalex.org/W2394377911","https://openalex.org/W63519562","https://openalex.org/W3020755331","https://openalex.org/W2593813247","https://openalex.org/W4386724243","https://openalex.org/W4388268408","https://openalex.org/W4387816319","https://openalex.org/W2016618709","https://openalex.org/W4380088563"],"abstract_inverted_index":{"To":[0],"minimize":[1],"the":[2,17,57,60,74,81,89,97,102,107,113,119,124,135,155,164,177,182],"negative":[3],"impacts":[4],"brought":[5],"by":[6,22,134,151,169,185],"floods,":[7],"researchers":[8],"from":[9],"pattern":[10],"recognition":[11],"community":[12],"pay":[13],"special":[14],"attention":[15],"to":[16,33,38,111,141,162],"problem":[18],"of":[19,25,59,91,106,118,148,154,166,181],"flood":[20],"prediction":[21],"involving":[23],"technologies":[24],"machine":[26],"learning.":[27],"In":[28],"this":[29],"paper,":[30],"we":[31,78,100,160],"propose":[32,161],"construct":[34],"hierarchical":[35,61],"Bayesian":[36,62,109,137,167],"network":[37,63,71,76,110,126,168],"predict":[39],"floods":[40],"for":[41,50,130,145],"small":[42,85],"rivers,":[43],"which":[44],"appropriately":[45],"embed":[46],"hydrology":[47,94],"expert":[48],"knowledge":[49],"high":[51],"rationality":[52],"and":[53,69,104,115,179],"robustness.":[54],"We":[55,175],"present":[56],"construction":[58],"in":[64],"two":[65],"stages":[66],"comprising":[67],"local":[68,75,86,108,131,136],"global":[70,125,156],"construction.":[72],"During":[73,123],"construction,":[77,127],"firstly":[79],"divide":[80],"river":[82],"watershed":[83],"into":[84],"regions.":[87],"Following":[88],"idea":[90],"a":[92,189],"famous":[93],"model":[95],"-":[96],"Xinanjiang":[98,120],"model,":[99,121],"establish":[101],"entities":[103],"connections":[105],"represent":[112],"variables":[114,129],"physical":[116],"processes":[117],"respectively.":[122],"intermediate":[128],"regions,":[132],"computed":[133],"network,":[138],"are":[139],"coupled":[140],"offer":[142],"an":[143],"estimation":[144],"time-varying":[146],"values":[147],"flow":[149,172],"rate":[150,173],"proper":[152],"inferences":[153],"network.":[157],"At":[158],"last,":[159],"improve":[163],"output":[165],"utilizing":[170],"former":[171],"values.":[174],"demonstrate":[176],"accuracy":[178],"robustness":[180],"proposed":[183],"method":[184],"conducting":[186],"experiments":[187],"on":[188],"collected":[190],"dataset":[191],"with":[192],"several":[193],"comparative":[194],"methods.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}