{"id":"https://openalex.org/W1975333498","doi":"https://doi.org/10.1109/coase.2014.6899462","title":"Applications of data assimilation to forecasting indoor environment","display_name":"Applications of data assimilation to forecasting indoor environment","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W1975333498","doi":"https://doi.org/10.1109/coase.2014.6899462","mag":"1975333498"},"language":"en","primary_location":{"id":"doi:10.1109/coase.2014.6899462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2014.6899462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102075057","display_name":"Cheng-Chun Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Cheng-Chun Lin","raw_affiliation_strings":["Concordia University, Montreal, Canada","Concordia University, Montreal, PQ H3G 1M8 Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Concordia University, Montreal, PQ H3G 1M8 Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076043035","display_name":"Liangzhu Wang","orcid":"https://orcid.org/0000-0002-0653-3612"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Liangzhu Wang","raw_affiliation_strings":["Concordia University, Montreal, Canada","Concordia University, Montreal, PQ H3G 1M8 Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Concordia University, Montreal, PQ H3G 1M8 Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.05509138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1097","last_page":"1102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11371","display_name":"Wind and Air Flow Studies","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11371","display_name":"Wind and Air Flow Studies","score":0.9994999766349792,"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/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10555","display_name":"Fire effects on ecosystems","score":0.9882000088691711,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/data-assimilation","display_name":"Data assimilation","score":0.9066480398178101},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.8461666107177734},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.5836625099182129},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5482809543609619},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5466381907463074},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5411196947097778},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4803275167942047},{"id":"https://openalex.org/keywords/numerical-weather-prediction","display_name":"Numerical weather prediction","score":0.4428614377975464},{"id":"https://openalex.org/keywords/assimilation","display_name":"Assimilation (phonology)","score":0.43574535846710205},{"id":"https://openalex.org/keywords/numerical-models","display_name":"Numerical models","score":0.41483795642852783},{"id":"https://openalex.org/keywords/computer-simulation","display_name":"Computer simulation","score":0.26150089502334595},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.23084339499473572},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22678130865097046},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.2254123091697693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.09959599375724792},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08421313762664795}],"concepts":[{"id":"https://openalex.org/C24552861","wikidata":"https://www.wikidata.org/wiki/Q2670177","display_name":"Data assimilation","level":2,"score":0.9066480398178101},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.8461666107177734},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.5836625099182129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5482809543609619},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5466381907463074},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5411196947097778},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4803275167942047},{"id":"https://openalex.org/C147947694","wikidata":"https://www.wikidata.org/wiki/Q837552","display_name":"Numerical weather prediction","level":2,"score":0.4428614377975464},{"id":"https://openalex.org/C75649859","wikidata":"https://www.wikidata.org/wiki/Q148877","display_name":"Assimilation (phonology)","level":2,"score":0.43574535846710205},{"id":"https://openalex.org/C2986605239","wikidata":"https://www.wikidata.org/wiki/Q925667","display_name":"Numerical models","level":3,"score":0.41483795642852783},{"id":"https://openalex.org/C500300565","wikidata":"https://www.wikidata.org/wiki/Q925667","display_name":"Computer simulation","level":2,"score":0.26150089502334595},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.23084339499473572},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22678130865097046},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.2254123091697693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.09959599375724792},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08421313762664795},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/coase.2014.6899462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2014.6899462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6000000238418579,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1544191831","https://openalex.org/W1565152710","https://openalex.org/W2008148715","https://openalex.org/W2016211524","https://openalex.org/W2072175500","https://openalex.org/W2089197874","https://openalex.org/W2105934661","https://openalex.org/W2108690142","https://openalex.org/W2147119488","https://openalex.org/W2149825759","https://openalex.org/W2150500052","https://openalex.org/W2157098139","https://openalex.org/W2166490913","https://openalex.org/W2623032470","https://openalex.org/W2736976344","https://openalex.org/W2790026458","https://openalex.org/W2793029655","https://openalex.org/W4232430184","https://openalex.org/W4285719527","https://openalex.org/W6698119764","https://openalex.org/W6749098633"],"related_works":["https://openalex.org/W4212971657","https://openalex.org/W1949985943","https://openalex.org/W2089385108","https://openalex.org/W2363380593","https://openalex.org/W2377052976","https://openalex.org/W2991541038","https://openalex.org/W2393565244","https://openalex.org/W1980785126","https://openalex.org/W2062890270","https://openalex.org/W788509307"],"abstract_inverted_index":{"Data":[0],"assimilation":[1,38],"(DA)":[2],"is":[3,26,44,75,121],"a":[4,82,87,129],"technique":[5],"to":[6,29,47,53,66,76,122,144],"combine":[7],"numerical":[8,22],"predictions":[9,153],"and":[10],"experimental":[11],"measurements,":[12],"which":[13],"has":[14],"been":[15],"commonly":[16],"used":[17],"by":[18,104],"the":[19,30,78,101,124,148,152],"community":[20],"of":[21,32,64],"weather":[23],"forecasting":[24,67],"but":[25],"relatively":[27],"new":[28,62],"field":[31],"indoor":[33,68],"environment.":[34],"Among":[35],"all":[36],"data":[37],"methods,":[39],"Ensemble":[40],"Kalman":[41],"Filter":[42],"(EnKF)":[43],"especially":[45],"suitable":[46],"solve":[48],"large-scale":[49],"nonlinear":[50],"problems":[51],"due":[52],"its":[54],"low":[55],"computation":[56],"requirement.":[57],"In":[58],"this":[59],"paper,":[60],"two":[61],"applications":[63],"EnKF":[65,110,149],"environment":[69],"are":[70],"presented.":[71],"The":[72,93,118],"first":[73],"study":[74,120],"forecast":[77,94,115],"contaminant":[79],"transport":[80],"in":[81,100,128],"residential":[83],"house":[84],"based":[85],"on":[86],"multi-room":[88,130],"tracer":[89],"gas":[90],"decay":[91],"experiment.":[92],"model":[95,107,141],"avoids":[96],"calculating":[97],"source":[98],"term":[99],"given":[102],"problem":[103],"rapid":[105],"updating":[106],"states":[108],"with":[109],"while":[111],"still":[112],"providing":[113],"significant":[114],"lead":[116],"time.":[117],"second":[119],"predict":[123],"fire":[125,132],"smoke":[126],"dispersion":[127],"compartment":[131],"without":[133],"giving":[134],"actual":[135],"heat":[136],"release":[137],"rates":[138],"(HRRs)":[139],"as":[140],"inputs.":[142],"Compared":[143],"conventional":[145],"deterministic":[146],"models,":[147],"models":[150],"improve":[151],"significantly.":[154]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}