{"id":"https://openalex.org/W2053372350","doi":"https://doi.org/10.1109/fskd.2010.5569765","title":"Fuzzy time series reflecting the fluctuation of historical data","display_name":"Fuzzy time series reflecting the fluctuation of historical data","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W2053372350","doi":"https://doi.org/10.1109/fskd.2010.5569765","mag":"2053372350"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2010.5569765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2010.5569765","pdf_url":null,"source":{"id":"https://openalex.org/S4363608217","display_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","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/A5079482972","display_name":"Hye-Young Jung","orcid":"https://orcid.org/0000-0003-0569-370X"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hye-young Jung","raw_affiliation_strings":["Department of Mathematics, Yonsei University, Seoul, South Korea","Department of Mathematics Yonsei University Seoul 120-749, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Department of Mathematics Yonsei University Seoul 120-749, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103968978","display_name":"J. H. Yoon","orcid":"https://orcid.org/0000-0001-7676-0821"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin-hee Yoon","raw_affiliation_strings":["School of Economics, Yonsei University, Seoul, South Korea","School of Economics, Yonsei University, Seoul 120-749, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Economics, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"School of Economics, Yonsei University, Seoul 120-749, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101203483","display_name":"Seung-Hoe Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I24456540","display_name":"Korea Aerospace University","ror":"https://ror.org/05jmm0651","country_code":"KR","type":"education","lineage":["https://openalex.org/I24456540"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seung-hoe Choi","raw_affiliation_strings":["School of Liberal arts and Science, Korea Aerospace University, Goyang, South Korea","School of Liberal arts and Science, Korea Aerospace University, Goyang 412-791, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Liberal arts and Science, Korea Aerospace University, Goyang, South Korea","institution_ids":["https://openalex.org/I24456540"]},{"raw_affiliation_string":"School of Liberal arts and Science, Korea Aerospace University, Goyang 412-791, South Korea","institution_ids":["https://openalex.org/I24456540"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5079482972"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":0.452,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.58728011,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"14","issue":null,"first_page":"473","last_page":"477"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/series","display_name":"Series (stratigraphy)","score":0.7057062387466431},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6732398867607117},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6478667259216309},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.6266894936561584},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6067405939102173},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5924628376960754},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5580028891563416},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5164104104042053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38084059953689575},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27636027336120605},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2667723298072815},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07459458708763123}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.7057062387466431},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6732398867607117},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6478667259216309},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.6266894936561584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6067405939102173},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5924628376960754},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5580028891563416},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5164104104042053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38084059953689575},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27636027336120605},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2667723298072815},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07459458708763123},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2010.5569765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2010.5569765","pdf_url":null,"source":{"id":"https://openalex.org/S4363608217","display_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1971869067","https://openalex.org/W1992096620","https://openalex.org/W1993503008","https://openalex.org/W2000507891","https://openalex.org/W2053612364","https://openalex.org/W2093842148","https://openalex.org/W2130519559","https://openalex.org/W2131453387","https://openalex.org/W4241443503"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4248336175","https://openalex.org/W2031260042","https://openalex.org/W2391445434","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"The":[0],"fuzzy":[1,28,75],"time":[2,15,76],"series":[3,16],"is":[4,85,91,103],"introduced":[5],"by":[6],"Song":[7],"and":[8,27,68,87,108],"Chissom":[9],"to":[10,38,61,69,105],"construct":[11],"a":[12],"pattern":[13],"for":[14],"with":[17,32],"vague":[18],"or":[19],"linguistic":[20],"value.":[21],"Many":[22],"methods":[23,107],"using":[24],"the":[25,40,49,57,63,71,79,82,88,97,112],"interval":[26,58],"logical":[29],"relationship":[30],"related":[31],"historical":[33,52,66,115],"data":[34,67],"have":[35],"been":[36],"suggested":[37],"enhance":[39],"forecasting":[41,72,89,101],"accuracy.":[42],"But":[43],"they":[44],"do":[45],"not":[46],"fully":[47,110],"reflect":[48,62],"fluctuation":[50,64,113],"of":[51,65,74,114],"data.":[53,116],"Therefore,":[54],"we":[55],"propose":[56],"rearranged":[59],"method":[60,84,99],"improve":[70],"accuracy":[73,90,102],"series.":[77],"Using":[78],"well-known":[80],"enrollment,":[81],"proposed":[83,98],"discussed":[86],"evaluated.":[92],"Empirical":[93],"analysis":[94],"shows":[95],"that":[96],"in":[100],"superior":[104],"existing":[106],"it":[109],"reflects":[111]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}