{"id":"https://openalex.org/W2809926842","doi":"https://doi.org/10.1109/fskd.2017.8393239","title":"Big data stream learning based on hybridized Kalman filter and backpropagation through time method","display_name":"Big data stream learning based on hybridized Kalman filter and backpropagation through time method","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2809926842","doi":"https://doi.org/10.1109/fskd.2017.8393239","mag":"2809926842"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2017.8393239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","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/A5026094492","display_name":"Fan He","orcid":"https://orcid.org/0000-0003-3497-3700"},"institutions":[{"id":"https://openalex.org/I82509713","display_name":"M\u00e4lardalen University","ror":"https://ror.org/033vfbz75","country_code":"SE","type":"education","lineage":["https://openalex.org/I82509713"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Fan He","raw_affiliation_strings":["School of Innovation, M\u00e4lardalen University, V\u00e4ster\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"School of Innovation, M\u00e4lardalen University, V\u00e4ster\u00e5s, Sweden","institution_ids":["https://openalex.org/I82509713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102290471","display_name":"Ning Xiong","orcid":"https://orcid.org/0000-0001-9857-4317"},"institutions":[{"id":"https://openalex.org/I82509713","display_name":"M\u00e4lardalen University","ror":"https://ror.org/033vfbz75","country_code":"SE","type":"education","lineage":["https://openalex.org/I82509713"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ning Xiong","raw_affiliation_strings":["School of Innovation, M\u00e4lardalen University, V\u00e4ster\u00e5s, Sweden"],"affiliations":[{"raw_affiliation_string":"School of Innovation, M\u00e4lardalen University, V\u00e4ster\u00e5s, Sweden","institution_ids":["https://openalex.org/I82509713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026094492"],"corresponding_institution_ids":["https://openalex.org/I82509713"],"apc_list":null,"apc_paid":null,"fwci":0.195,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65955148,"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":"2886","last_page":"2891"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9850999712944031,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9850999712944031,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9812999963760376,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9764000177383423,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.8439304828643799},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.805946946144104},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.7032116055488586},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.7012941241264343},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6343656778335571},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5742201209068298},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5066536068916321},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4768684506416321},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4425889849662781},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4422968029975891},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41808217763900757},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10494515299797058}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8439304828643799},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.805946946144104},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.7032116055488586},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.7012941241264343},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6343656778335571},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5742201209068298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5066536068916321},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4768684506416321},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4425889849662781},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4422968029975891},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41808217763900757},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10494515299797058},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2017.8393239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1490878211","https://openalex.org/W1557776678","https://openalex.org/W1665214252","https://openalex.org/W1968140153","https://openalex.org/W1978581090","https://openalex.org/W2010767552","https://openalex.org/W2041495685","https://openalex.org/W2056992242","https://openalex.org/W2057503036","https://openalex.org/W2097074201","https://openalex.org/W2124649758","https://openalex.org/W2186879008","https://openalex.org/W2506822277","https://openalex.org/W2554861503","https://openalex.org/W2585503147","https://openalex.org/W3206971523","https://openalex.org/W4252760031","https://openalex.org/W6637242042","https://openalex.org/W6730045385","https://openalex.org/W6732339152"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W4239286941","https://openalex.org/W2088845016","https://openalex.org/W589102260","https://openalex.org/W1966421350","https://openalex.org/W1863534956","https://openalex.org/W2128396103","https://openalex.org/W1868434454","https://openalex.org/W4225394202","https://openalex.org/W4366984740"],"abstract_inverted_index":{"Most":[0],"real-time":[1,27],"control":[2],"systems":[3],"are":[4],"often":[5],"accompanied":[6],"with":[7],"various":[8],"changes":[9,17,129],"such":[10,72],"as":[11,53],"variations":[12],"of":[13,18,43,71,81,87,130],"working":[14],"load":[15],"and":[16,84,109],"the":[19,32,69,88,100],"environment.":[20],"Hence":[21],"it":[22],"is":[23],"necessary":[24],"to":[25,39,97,128],"perform":[26],"process":[28,50,123],"modeling":[29,118],"so":[30],"that":[31,99],"model":[33,51],"can":[34,113],"adjust":[35],"itself":[36],"in":[37,132],"runtime":[38],"maintain":[40],"high":[41,107,117],"accuracy":[42,108,119],"states":[44],"under":[45],"control.":[46],"This":[47],"paper":[48],"considers":[49],"represented":[52],"a":[54,61,121,133],"deep":[55],"recurrent":[56,73],"neural":[57,74],"network.":[58],"We":[59],"propose":[60],"new":[62],"hybridized":[63],"learning":[64,102],"method":[65,103],"for":[66,120],"online":[67],"updating":[68],"weights":[70],"networks":[75],"by":[76],"exploiting":[77],"both":[78],"fast":[79,105],"convergence":[80],"Kalman":[82],"filter":[83],"stable":[85],"search":[86],"Backpropagation":[89],"through":[90],"time":[91],"algorithm.":[92],"Several":[93],"experiments":[94],"were":[95],"made":[96],"show":[98],"proposed":[101],"has":[104],"convergence,":[106],"good":[110],"adaptivity.":[111],"It":[112],"not":[114],"only":[115],"achieve":[116],"static":[122],"but":[124],"also":[125],"quickly":[126],"adapt":[127],"characteristics":[131],"time-varying":[134],"process.":[135]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}