{"id":"https://openalex.org/W1673053763","doi":"https://doi.org/10.3233/ifs-1997-5102","title":"Short-Term Prediction of Chaotic Time Series by Local Fuzzy Reconstruction Method","display_name":"Short-Term Prediction of Chaotic Time Series by Local Fuzzy Reconstruction Method","publication_year":1997,"publication_date":"1997-02-01","ids":{"openalex":"https://openalex.org/W1673053763","doi":"https://doi.org/10.3233/ifs-1997-5102","mag":"1673053763"},"language":"en","primary_location":{"id":"doi:10.3233/ifs-1997-5102","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ifs-1997-5102","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-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/A5088201194","display_name":"Tadashi Iokibe","orcid":null},"institutions":[{"id":"https://openalex.org/I101979096","display_name":"Meidensha (Japan)","ror":"https://ror.org/047dt4g31","country_code":"JP","type":"company","lineage":["https://openalex.org/I101979096"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"T. Iokibe","raw_affiliation_strings":["Meidensha Corporation, 36-2 Nihonbashi Hakozaki-cho, Chuo-ku, Tokyo 103, Japan","Meidensha Corporation, 36-2 Nihonbashi Hakozaki-cho, Chuo-ku, Tokyo 103, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"Meidensha Corporation, 36-2 Nihonbashi Hakozaki-cho, Chuo-ku, Tokyo 103, Japan","institution_ids":["https://openalex.org/I101979096"]},{"raw_affiliation_string":"Meidensha Corporation, 36-2 Nihonbashi Hakozaki-cho, Chuo-ku, Tokyo 103, Japan#TAB#","institution_ids":["https://openalex.org/I101979096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014348297","display_name":"Yasunari Fujimoto","orcid":null},"institutions":[{"id":"https://openalex.org/I101979096","display_name":"Meidensha (Japan)","ror":"https://ror.org/047dt4g31","country_code":"JP","type":"company","lineage":["https://openalex.org/I101979096"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Y. Fujimoto","raw_affiliation_strings":["Meidensha Corporation, 36-2 Nihonbashi Hakozaki-cho, Chuo-ku, Tokyo 103, Japan","Meidensha Corporation, 36-2 Nihonbashi Hakozaki-cho, Chuo-ku, Tokyo 103, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"Meidensha Corporation, 36-2 Nihonbashi Hakozaki-cho, Chuo-ku, Tokyo 103, Japan","institution_ids":["https://openalex.org/I101979096"]},{"raw_affiliation_string":"Meidensha Corporation, 36-2 Nihonbashi Hakozaki-cho, Chuo-ku, Tokyo 103, Japan#TAB#","institution_ids":["https://openalex.org/I101979096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045369016","display_name":"Masayasu Kanke","orcid":null},"institutions":[{"id":"https://openalex.org/I101979096","display_name":"Meidensha (Japan)","ror":"https://ror.org/047dt4g31","country_code":"JP","type":"company","lineage":["https://openalex.org/I101979096"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"M. Kanke","raw_affiliation_strings":["Meidensha Corporation, 127 Nishishin-machi, Ohta 373, Japan","Meidensha Corporation, 127 Nishishin-machi, Ohta 373, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"Meidensha Corporation, 127 Nishishin-machi, Ohta 373, Japan","institution_ids":["https://openalex.org/I101979096"]},{"raw_affiliation_string":"Meidensha Corporation, 127 Nishishin-machi, Ohta 373, Japan#TAB#","institution_ids":["https://openalex.org/I101979096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113526363","display_name":"S. Suzuki","orcid":"https://orcid.org/0009-0008-5655-1238"},"institutions":[{"id":"https://openalex.org/I101979096","display_name":"Meidensha (Japan)","ror":"https://ror.org/047dt4g31","country_code":"JP","type":"company","lineage":["https://openalex.org/I101979096"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"S. Suzuki","raw_affiliation_strings":["Meiden Software Corporation, Nishibiwajima-cho, Kasugai-gun, Aichi 452, Japan","Meiden Software Corporation, Nishibiwajima-cho, Kasugai-gun, Aichi 452, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"Meiden Software Corporation, Nishibiwajima-cho, Kasugai-gun, Aichi 452, Japan","institution_ids":["https://openalex.org/I101979096"]},{"raw_affiliation_string":"Meiden Software Corporation, Nishibiwajima-cho, Kasugai-gun, Aichi 452, Japan#TAB#","institution_ids":["https://openalex.org/I101979096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5088201194"],"corresponding_institution_ids":["https://openalex.org/I101979096"],"apc_list":null,"apc_paid":null,"fwci":1.0712,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.72352257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"5","issue":"1","first_page":"3","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10244","display_name":"Chaos control and synchronization","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10244","display_name":"Chaos control and synchronization","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9968000054359436,"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/T10320","display_name":"Neural Networks and Applications","score":0.9660999774932861,"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/term","display_name":"Term (time)","score":0.7806791663169861},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.7235994935035706},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6792358160018921},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6100807785987854},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5667888522148132},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5523236989974976},{"id":"https://openalex.org/keywords/long-term-prediction","display_name":"Long-term prediction","score":0.4786994755268097},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38501986861228943},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32814204692840576},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.311359167098999},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17775845527648926},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08058634400367737},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.05313846468925476},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.04289513826370239}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.7806791663169861},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.7235994935035706},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6792358160018921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6100807785987854},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5667888522148132},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5523236989974976},{"id":"https://openalex.org/C2776537626","wikidata":"https://www.wikidata.org/wiki/Q4047883","display_name":"Long-term prediction","level":2,"score":0.4786994755268097},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38501986861228943},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32814204692840576},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.311359167098999},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17775845527648926},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08058634400367737},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.05313846468925476},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.04289513826370239},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ifs-1997-5102","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ifs-1997-5102","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1966762086","https://openalex.org/W2087627382","https://openalex.org/W2141394518","https://openalex.org/W3162981193","https://openalex.org/W4299993032"],"related_works":["https://openalex.org/W2622688551","https://openalex.org/W2119012848","https://openalex.org/W1990205660","https://openalex.org/W1550175370","https://openalex.org/W4387331850","https://openalex.org/W2393769591","https://openalex.org/W1974708359","https://openalex.org/W2162883116","https://openalex.org/W2325790386","https://openalex.org/W2015977711"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,20,52,58,61,74,82,86,89,93,99,110,115,126,135,141,144,152,166,179,196,199,207,211,215],"study":[4],"of":[5,19,40,77,102,147,154,184,195,198,210],"chaos":[6,12],"has":[7,140],"been":[8],"drawing":[9],"attention.":[10],"As":[11],"application,":[13],"we":[14,172,177],"propose":[15],"a":[16,35,68,185],"short-term":[17,182,208],"prediction":[18,27,56,104,122,183,209],"time":[21,63,145,187,224],"series":[22,64,188],"under":[23],"chaotic":[24,186,223],"behavior.":[25],"Short-term":[26,55],"is":[28,65,81,120,130,193],"to":[29,73,117,181,206],"find":[30],"some":[31],"deterministic":[32,174],"regularity":[33],"in":[34,51,67,189],"phenomenon":[36],"that":[37,84,121,143],"was":[38],"thought":[39],"as":[41,98,151,221,237],"noise":[42],"or":[43],"an":[44],"irregularity":[45],"and":[46,214,226,233],"thereby":[47],"predict":[48],"its":[49],"state":[50,70,156],"near":[53],"future.":[54],"employs":[57],"following":[59],"technique:":[60],"observed":[62,95],"reconstructed":[66,155],"multidimensional":[69],"space":[71,157],"according":[72],"Takens'":[75],"theorem":[76],"embedding.":[78],"Local":[79],"reconstruction":[80,169,203],"mode":[83],"uses":[85],"vector":[87,129],"neighboring":[88,128],"data":[90,236],"vector,":[91],"including":[92],"latest":[94],"data.":[96],"Proposed":[97],"practical":[100],"methods":[101,119],"this":[103,163],"are":[105,219],"Gram-Schmidt's":[106],"orthogonal":[107],"system":[108],"method,":[109,112,137],"tessellation":[111,136],"etc.":[113],"However,":[114],"drawback":[116],"these":[118],"becomes":[123],"impossible":[124],"if":[125],"selected":[127],"not":[131],"linearly":[132],"independent.":[133],"1n":[134],"it":[138],"also":[139],"shortcoming":[142],"period":[146],"calculation":[148],"increases":[149],"abruptly":[150],"dimension":[153],"increases.":[158],"To":[159],"overcome":[160],"such":[161],"disadvantages,":[162],"article":[164],"proposes":[165],"local":[167,201],"fuzzy":[168,202],"method.":[170],"First":[171],"explain":[173],"chaos.":[175],"Next":[176],"show":[178],"approach":[180],"detail.":[190],"Finally,":[191],"examination":[192],"made":[194],"result":[197],"preceding":[200],"method":[204],"applied":[205],"logistic":[212],"map":[213],"Lorenz":[216],"attractor,":[217],"which":[218],"known":[220],"typical":[222],"series,":[225],"tap":[227],"water":[228],"demand":[229,235],"data,":[230],"traffic":[231],"density,":[232],"power":[234],"social":[238],"phenomena.":[239]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
