{"id":"https://openalex.org/W4306746295","doi":"https://doi.org/10.3233/jifs-222721","title":"Establish a trend fuzzy information granule based short-term forecasting with long-association and k-medoids clustering","display_name":"Establish a trend fuzzy information granule based short-term forecasting with long-association and k-medoids clustering","publication_year":2022,"publication_date":"2022-10-18","ids":{"openalex":"https://openalex.org/W4306746295","doi":"https://doi.org/10.3233/jifs-222721"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-222721","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-222721","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 & 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/A5100394192","display_name":"Fang Li","orcid":"https://orcid.org/0000-0002-6401-284X"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fang Li","raw_affiliation_strings":["Department of Mathematics, College of Arts and Sciences, Shanghai Maritime University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, College of Arts and Sciences, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103662857","display_name":"Weihua Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Lu","raw_affiliation_strings":["Department of Mathematics, College of Arts and Sciences, Shanghai Maritime University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, College of Arts and Sciences, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056718487","display_name":"Xiyang Yang","orcid":"https://orcid.org/0000-0002-9790-8992"},"institutions":[{"id":"https://openalex.org/I169019527","display_name":"Quanzhou Normal University","ror":"https://ror.org/006ak0b38","country_code":"CN","type":"education","lineage":["https://openalex.org/I169019527"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiyang Yang","raw_affiliation_strings":["Fujian Provincial Key Laboratory of Data Intensive Computing, Quanzhou Normal University, Quanzhou, China"],"affiliations":[{"raw_affiliation_string":"Fujian Provincial Key Laboratory of Data Intensive Computing, Quanzhou Normal University, Quanzhou, China","institution_ids":["https://openalex.org/I169019527"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102956230","display_name":"Chong Guo","orcid":"https://orcid.org/0000-0003-4341-787X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chong Guo","raw_affiliation_strings":["Yangshan Port Maritime Safety Administration, Shanghai, Shanghai, China","E-mail:"],"affiliations":[{"raw_affiliation_string":"Yangshan Port Maritime Safety Administration, Shanghai, Shanghai, China","institution_ids":[]},{"raw_affiliation_string":"E-mail:","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100394192"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":null,"apc_paid":null,"fwci":0.2975,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51390528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"44","issue":"1","first_page":"1397","last_page":"1411"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9952999949455261,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9952999949455261,"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"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9934999942779541,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9873999953269958,"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/association-rule-learning","display_name":"Association rule learning","score":0.7479478120803833},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5957844853401184},{"id":"https://openalex.org/keywords/premise","display_name":"Premise","score":0.5774702429771423},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5771313905715942},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5296240448951721},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5000414848327637},{"id":"https://openalex.org/keywords/granular-computing","display_name":"Granular computing","score":0.41894322633743286},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3878583312034607},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.1503988802433014}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.7479478120803833},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5957844853401184},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.5774702429771423},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5771313905715942},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5296240448951721},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5000414848327637},{"id":"https://openalex.org/C17209119","wikidata":"https://www.wikidata.org/wiki/Q5596712","display_name":"Granular computing","level":3,"score":0.41894322633743286},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3878583312034607},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.1503988802433014},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-222721","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-222721","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 & 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":37,"referenced_works":["https://openalex.org/W1793999168","https://openalex.org/W1979464351","https://openalex.org/W1979637725","https://openalex.org/W2001339767","https://openalex.org/W2018113971","https://openalex.org/W2030103549","https://openalex.org/W2034363911","https://openalex.org/W2043429280","https://openalex.org/W2065283082","https://openalex.org/W2094138658","https://openalex.org/W2254011497","https://openalex.org/W2396180393","https://openalex.org/W2546286828","https://openalex.org/W2550257869","https://openalex.org/W2618729590","https://openalex.org/W2758138366","https://openalex.org/W2765904007","https://openalex.org/W2783290031","https://openalex.org/W2787084639","https://openalex.org/W2897998689","https://openalex.org/W2914506313","https://openalex.org/W2917506610","https://openalex.org/W2980762031","https://openalex.org/W2985480822","https://openalex.org/W2991579784","https://openalex.org/W2997687596","https://openalex.org/W3004346138","https://openalex.org/W3007211815","https://openalex.org/W3010704712","https://openalex.org/W3081450554","https://openalex.org/W3083628579","https://openalex.org/W3095561022","https://openalex.org/W3136075374","https://openalex.org/W3165444694","https://openalex.org/W3194074702","https://openalex.org/W4236380464","https://openalex.org/W6772194416"],"related_works":["https://openalex.org/W2347219288","https://openalex.org/W2375956775","https://openalex.org/W2370203199","https://openalex.org/W2361925972","https://openalex.org/W1997725546","https://openalex.org/W2009718752","https://openalex.org/W2052173452","https://openalex.org/W13053856","https://openalex.org/W2348097614","https://openalex.org/W1772078940"],"abstract_inverted_index":{"In":[0],"the":[1,14,26,48,68,79,103,113,128,152,156,161,172,195,203,212,217],"existing":[2,104,162,173,244],"short-term":[3,179,199],"forecasting":[4,180,187,232],"methods":[5],"of":[6,16,125,130,206,234],"time":[7,62,75,91,100,149],"series,":[8,76],"two":[9],"challenges":[10],"are":[11,141,209,226],"faced:":[12],"capture":[13],"associations":[15],"data":[17],"and":[18,64,85,98,191,228],"avoid":[19],"cumulative":[20,196],"errors.":[21],"For":[22],"tackling":[23],"these":[24,139],"challenges,":[25],"fuzzy":[27,42,114,144,167],"information":[28,145],"granule":[29,55,59,84,88],"based":[30,220],"model":[31,40,181,185,208,236],"catches":[32],"our":[33],"attention.":[34],"The":[35,230],"rule":[36,44,116,126,169,221],"used":[37],"in":[38,46,70,73,96,120,158,198,246],"this":[39,121,207,235],"is":[41,50,118,164,182],"association":[43,80],"(FAR),":[45],"which":[47],"FAR":[49,105,163],"constructed":[51],"from":[52,211],"a":[53,57,82,86,135,177],"premise":[54,83],"to":[56],"consequent":[58,87,136],"at":[60,89,147,188],"consecutive":[61],"periods,":[63,92],"then":[65,192],"it":[66,193,242],"describes":[67],"short-association":[69,168],"data.":[71,159],"However,":[72],"real":[74],"another":[77],"association,":[78],"between":[81],"non-consecutive":[90,148],"frequently":[93],"exists,":[94],"especially":[95],"periodical":[97],"seasonal":[99],"series.":[101],"While":[102],"can\u2019t":[106],"express":[107],"such":[108],"association.":[109],"To":[110],"describe":[111,155],"it,":[112],"long-association":[115,157],"(FLAR)":[117],"proposed":[119],"study.":[122],"This":[123,184],"kind":[124],"reflects":[127],"influence":[129],"an":[131],"antecedent":[132],"trend":[133],"on":[134],"trend,":[137],"where":[138],"trends":[140],"described":[142],"by":[143,216,240],"granules":[146],"periods.":[150],"Thus,":[151],"FLAR":[153],"can":[154],"Correspondingly,":[160],"called":[165],"as":[166],"(FSAR).":[170],"Combining":[171],"FSAR":[174],"with":[175,243],"FLAR,":[176],"novel":[178],"presented.":[183],"makes":[186],"granular":[189],"level,":[190],"reduces":[194],"errors":[197],"prediction.":[200],"Note":[201],"that":[202],"prediction":[204],"results":[205],"calculated":[210],"available":[213],"FARs":[214],"selected":[215],"k-medoids":[218],"clustering":[219],"selection":[222],"algorithm,":[223],"therefore":[224],"they":[225],"logical":[227],"accurate.":[229],"better":[231],"performance":[233],"has":[237],"been":[238],"verified":[239],"comparing":[241],"models":[245],"experiments.":[247]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}