{"id":"https://openalex.org/W2902800417","doi":"https://doi.org/10.3233/978-1-61499-927-0-553","title":"Application of Fuzzy Control to Observational Error Covariance Matrices for Data Assimilation","display_name":"Application of Fuzzy Control to Observational Error Covariance Matrices for Data Assimilation","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2902800417","doi":"https://doi.org/10.3233/978-1-61499-927-0-553","mag":"2902800417"},"language":"en","primary_location":{"id":"doi:10.3233/978-1-61499-927-0-553","is_oa":false,"landing_page_url":"https://doi.org/10.3233/978-1-61499-927-0-553","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","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/A5026108247","display_name":"Yulong Bai","orcid":"https://orcid.org/0009-0001-7106-8518"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai Yu-Long","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090727170","display_name":"Chang Ming-heng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang Ming-heng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101024095","display_name":"Xu Baoxiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu Bao-xiong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5049710229","display_name":"Yongjie Ma","orcid":"https://orcid.org/0000-0002-5062-9224"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma Yong-jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.08500483,"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":"553","last_page":"562"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11325","display_name":"Inertial Sensor and Navigation","score":0.8610000014305115,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11325","display_name":"Inertial Sensor and Navigation","score":0.8610000014305115,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10320","display_name":"Neural Networks and Applications","score":0.8460000157356262,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.8352000117301941,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/covariance","display_name":"Covariance","score":0.6785888671875},{"id":"https://openalex.org/keywords/assimilation","display_name":"Assimilation (phonology)","score":0.5926578640937805},{"id":"https://openalex.org/keywords/data-assimilation","display_name":"Data assimilation","score":0.5704605579376221},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.539954662322998},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47926899790763855},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4771254062652588},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.46396055817604065},{"id":"https://openalex.org/keywords/covariance-intersection","display_name":"Covariance intersection","score":0.4220130443572998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3869993984699249},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3817983567714691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2773706912994385},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.22023987770080566},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.18476247787475586},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.11578384041786194},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08586567640304565},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.06664872169494629}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6785888671875},{"id":"https://openalex.org/C75649859","wikidata":"https://www.wikidata.org/wiki/Q148877","display_name":"Assimilation (phonology)","level":2,"score":0.5926578640937805},{"id":"https://openalex.org/C24552861","wikidata":"https://www.wikidata.org/wiki/Q2670177","display_name":"Data assimilation","level":2,"score":0.5704605579376221},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.539954662322998},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47926899790763855},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4771254062652588},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.46396055817604065},{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.4220130443572998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3869993984699249},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3817983567714691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2773706912994385},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.22023987770080566},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.18476247787475586},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.11578384041786194},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08586567640304565},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.06664872169494629}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3233/978-1-61499-927-0-553","is_oa":false,"landing_page_url":"https://doi.org/10.3233/978-1-61499-927-0-553","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},{"id":"mag:2902800417","is_oa":false,"landing_page_url":"https://dblp.uni-trier.de/db/conf/fsdm/fsdm2018.html#BaiCXM18","pdf_url":null,"source":{"id":"https://openalex.org/S4306510962","display_name":"FSDM","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"FSDM","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2718384077","https://openalex.org/W1597192237","https://openalex.org/W2022823194","https://openalex.org/W2317323511","https://openalex.org/W2394447903","https://openalex.org/W2890621699","https://openalex.org/W4238891807","https://openalex.org/W2395573186","https://openalex.org/W2170838091","https://openalex.org/W338040569"],"abstract_inverted_index":{"This":[0],"article":[1],"reviews":[2],"the":[3,58,64,68,86,89,94,100,113,120,128,138,141,146,149,153,158,166],"characteristics":[4],"of":[5,88,127,137,148],"two":[6,90],"common":[7,167],"localization":[8,17,70],"methods":[9,66],"in":[10,57],"ensemble":[11],"Kalman":[12],"filter":[13],"(EnKF)":[14],"systems:":[15],"covariance":[16,97,131],"(CL)":[18],"and":[19,44,99],"local":[20],"analysis":[21],"(LA).":[22],"To":[23,84],"obtain":[24],"better":[25],"assimilation":[26,31,139],"results,":[27],"a":[28,75,108],"new":[29,91,121,150,159],"data":[30],"system":[32],"coupled":[33],"with":[34,134],"fuzzy":[35,50],"control":[36,51,59],"algorithms":[37,92,122],"is":[38],"proposed,":[39],"named":[40],"CF":[41],"(covariance":[42],"fuzzy)":[43],"FA":[45],"(fuzzy":[46],"analysis).":[47],"Motivated":[48],"by":[49,145],"concepts":[52],"that":[53,119,157],"have":[54],"been":[55],"developed":[56],"engineering":[60],"field":[61],"for":[62],"years,":[63],"proposed":[65],"improve":[67],"normal":[69],"method":[71],"which":[72],"behaves":[73],"like":[74],"Gaussian":[76],"function":[77],"but":[78],"reaches":[79],"zero":[80],"at":[81],"finite":[82],"radius.":[83],"explore":[85],"effects":[87],"on":[93],"background":[95,129],"error":[96,130],"matrix":[98,143],"gain":[101,142],"matrix,":[102],"numerical":[103],"experiments":[104,117],"are":[105],"designed":[106],"using":[107],"classical":[109],"nonlinear":[110],"model":[111],"(i.e.,":[112],"Lorenz-96":[114],"model).":[115],"The":[116],"show":[118],"can":[123],"eliminate":[124],"spurious":[125],"correlation":[126],"matrix.":[132],"Additionally,":[133],"an":[135],"increase":[136],"intensity,":[140],"followed":[144],"update":[147],"algorithm.":[151,168],"Finally,":[152],"experimental":[154],"results":[155],"demonstrate":[156],"algorithm":[160],"has":[161],"more":[162],"robust":[163],"performance":[164],"than":[165]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2018-12-11T00:00:00"}