{"id":"https://openalex.org/W1990989116","doi":"https://doi.org/10.1109/fuzz-ieee.2013.6622517","title":"Online learning and prediction of data streams using dynamically evolving fuzzy approach","display_name":"Online learning and prediction of data streams using dynamically evolving fuzzy approach","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W1990989116","doi":"https://doi.org/10.1109/fuzz-ieee.2013.6622517","mag":"1990989116"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2013.6622517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2013.6622517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5076245454","display_name":"Rashmi Dutta Baruah","orcid":"https://orcid.org/0000-0002-6756-8157"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Rashmi Dutta Baruah","raw_affiliation_strings":["School of Computing and Communications, Lancaster University, Lancaster, UK","Sch. of Comput. & Commun., Lancaster Univ., Lancaster, UK#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Computing and Communications, Lancaster University, Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Sch. of Comput. & Commun., Lancaster Univ., Lancaster, UK#TAB#","institution_ids":["https://openalex.org/I67415387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039480864","display_name":"Plamen Angelov","orcid":"https://orcid.org/0000-0002-5770-934X"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Plamen Angelov","raw_affiliation_strings":["School of Computing and Communications, Lancaster University, Lancaster, UK","Sch. of Comput. & Commun., Lancaster Univ., Lancaster, UK#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Computing and Communications, Lancaster University, Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Sch. of Comput. & Commun., Lancaster Univ., Lancaster, UK#TAB#","institution_ids":["https://openalex.org/I67415387"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076245454"],"corresponding_institution_ids":["https://openalex.org/I67415387"],"apc_list":null,"apc_paid":null,"fwci":3.7994,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.93340976,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9998999834060669,"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":0.993399977684021,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9817000031471252,"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/computer-science","display_name":"Computer science","score":0.8123838901519775},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7091155052185059},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6326310634613037},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.597326934337616},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5614197850227356},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.552642285823822},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5330580472946167},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.5010337829589844},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4955962896347046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45494887232780457},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44162222743034363},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.4386398196220398},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.4359259009361267},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.42123791575431824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8123838901519775},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7091155052185059},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6326310634613037},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.597326934337616},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5614197850227356},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.552642285823822},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5330580472946167},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.5010337829589844},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4955962896347046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45494887232780457},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44162222743034363},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.4386398196220398},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.4359259009361267},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.42123791575431824},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2013.6622517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2013.6622517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G643151945","display_name":null,"funder_award_id":"EP/D077680/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W43637044","https://openalex.org/W158884020","https://openalex.org/W182707955","https://openalex.org/W322952782","https://openalex.org/W1529021355","https://openalex.org/W1570834090","https://openalex.org/W1575097427","https://openalex.org/W1934919341","https://openalex.org/W1965198822","https://openalex.org/W1984049995","https://openalex.org/W1985504684","https://openalex.org/W1987193542","https://openalex.org/W1989874712","https://openalex.org/W1990368529","https://openalex.org/W1997101808","https://openalex.org/W2000328037","https://openalex.org/W2007042673","https://openalex.org/W2013357884","https://openalex.org/W2052201135","https://openalex.org/W2086775121","https://openalex.org/W2094603430","https://openalex.org/W2097973719","https://openalex.org/W2107082000","https://openalex.org/W2113076747","https://openalex.org/W2114651920","https://openalex.org/W2119939946","https://openalex.org/W2129013743","https://openalex.org/W2136340804","https://openalex.org/W2143402976","https://openalex.org/W2148285045","https://openalex.org/W2151863350","https://openalex.org/W2152161790","https://openalex.org/W2162635690","https://openalex.org/W4250859275"],"related_works":["https://openalex.org/W4281572076","https://openalex.org/W4307392573","https://openalex.org/W2802243998","https://openalex.org/W2736127210","https://openalex.org/W4389449520","https://openalex.org/W2060628068","https://openalex.org/W3208495060","https://openalex.org/W2277307313","https://openalex.org/W4246591448","https://openalex.org/W2235038291"],"abstract_inverted_index":{"Learning":[0],"and":[1,38,60,99,126,145,159,176],"prediction":[2],"in":[3,17,43,123,129],"a":[4,30,68,104,131],"data":[5,16,86,117,125],"streaming":[6,53],"environment":[7,54],"is":[8,107,121,141],"challenging":[9],"due":[10],"to":[11,101,108,148],"continuous":[12],"arrival":[13],"of":[14,52,115],"enormous":[15],"high":[18],"speed":[19],"that":[20,36,82,133,163],"often":[21],"evolves":[22],"with":[23,137],"time.":[24,138],"In":[25],"this":[26,94],"paper":[27],"we":[28],"present":[29],"dynamically":[31,71],"evolving":[32,72],"fuzzy":[33,64],"rule-based":[34],"model":[35,65],"predicts":[37],"learns":[39],"from":[40,90],"each":[41],"instance":[42],"the":[44,49,77,85,113,116,119,151,164,179],"stream,":[45,118],"taking":[46],"into":[47],"account":[48],"principal":[50],"issues":[51],"viz.,":[55],"limited":[56],"memory,":[57],"real":[58,152,160],"time,":[59],"dynamic":[61],"nature.":[62],"The":[63,154],"essentially":[66],"uses":[67],"newly":[69],"proposed":[70,165],"clustering":[73],"method":[74],"for":[75],"learning":[76],"structure.":[78],"Unlike":[79],"other":[80],"approaches":[81,175],"consider":[83],"either":[84],"density":[87,98,120],"or":[88,171],"distance":[89,100],"existing":[91,174],"cluster":[92,106],"centres,":[93],"approach":[95,166],"considers":[96],"both":[97,124],"decide":[102],"if":[103],"new":[105],"be":[109],"generated.":[110],"To":[111],"capture":[112],"dynamics":[114],"defined":[122],"time":[127],"space":[128],"such":[130],"way":[132],"it":[134],"decays":[135],"exponentially":[136],"A":[139],"distinction":[140],"made":[142],"between":[143],"core":[144],"non-core":[146],"clusters":[147],"effectively":[149],"identify":[150],"outliers.":[153],"experimental":[155],"results":[156,168],"using":[157],"benchmark":[158],"datasets":[161],"show":[162],"attains":[167],"at":[169],"par":[170],"better":[172],"than":[173],"significantly":[177],"reduces":[178],"computational":[180],"overhead.":[181]},"counts_by_year":[{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}