{"id":"https://openalex.org/W3207929357","doi":"https://doi.org/10.3233/jifs-211405","title":"Implement multi-step-ahead forecasting with multi-point association fuzzy logical relationship for time series","display_name":"Implement multi-step-ahead forecasting with multi-point association fuzzy logical relationship for time series","publication_year":2021,"publication_date":"2021-10-20","ids":{"openalex":"https://openalex.org/W3207929357","doi":"https://doi.org/10.3233/jifs-211405","mag":"3207929357"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-211405","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-211405","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/A5026674606","display_name":"Fang Li","orcid":"https://orcid.org/0000-0002-5061-2510"},"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/A5100414899","display_name":"Lihua Zhang","orcid":"https://orcid.org/0000-0002-3869-4795"},"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":"Lihua Zhang","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/A5061363420","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0002-0663-6865"},"institutions":[{"id":"https://openalex.org/I130541836","display_name":"Beijing Institute of Petrochemical Technology","ror":"https://ror.org/025s55q11","country_code":"CN","type":"education","lineage":["https://openalex.org/I130541836"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["School of Economics and Management, Beijing Institute of Petrochemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beijing Institute of Petrochemical Technology, Beijing, China","institution_ids":["https://openalex.org/I130541836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052943993","display_name":"Shihu Liu","orcid":"https://orcid.org/0000-0002-4442-5057"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihu Liu","raw_affiliation_strings":["School of Mathematics and Computer Sciences, Yunnan Minzu University, Kunming, China","E-mail:"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Sciences, Yunnan Minzu University, Kunming, China","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"E-mail:","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5026674606"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18542715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"42","issue":"3","first_page":"2023","last_page":"2039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9997000098228455,"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":0.9997000098228455,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.7685223817825317},{"id":"https://openalex.org/keywords/premise","display_name":"Premise","score":0.6366092562675476},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6322322487831116},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6098330020904541},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5941817760467529},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.5685425996780396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.557438313961029},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.49091655015945435},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4568004310131073},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3971789479255676},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3916774392127991},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3406447768211365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31078386306762695},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20093101263046265},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.12415564060211182}],"concepts":[{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.7685223817825317},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.6366092562675476},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6322322487831116},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6098330020904541},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5941817760467529},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.5685425996780396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.557438313961029},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.49091655015945435},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4568004310131073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3971789479255676},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3916774392127991},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3406447768211365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31078386306762695},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20093101263046265},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.12415564060211182},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-211405","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-211405","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":44,"referenced_works":["https://openalex.org/W1125761772","https://openalex.org/W1489782390","https://openalex.org/W1971619052","https://openalex.org/W2017954768","https://openalex.org/W2023764891","https://openalex.org/W2041598452","https://openalex.org/W2080504790","https://openalex.org/W2081747552","https://openalex.org/W2081874651","https://openalex.org/W2093574775","https://openalex.org/W2094475321","https://openalex.org/W2131453387","https://openalex.org/W2297745799","https://openalex.org/W2342393330","https://openalex.org/W2405867055","https://openalex.org/W2409641346","https://openalex.org/W2493064984","https://openalex.org/W2550257869","https://openalex.org/W2560606761","https://openalex.org/W2606450053","https://openalex.org/W2746076170","https://openalex.org/W2760087883","https://openalex.org/W2770882920","https://openalex.org/W2782299476","https://openalex.org/W2789534245","https://openalex.org/W2794923481","https://openalex.org/W2800753560","https://openalex.org/W2804281078","https://openalex.org/W2804382981","https://openalex.org/W2829556518","https://openalex.org/W2888185378","https://openalex.org/W2902141129","https://openalex.org/W2907419252","https://openalex.org/W2914924619","https://openalex.org/W2916408396","https://openalex.org/W2971337047","https://openalex.org/W3007203411","https://openalex.org/W3009888411","https://openalex.org/W3040453902","https://openalex.org/W3041310133","https://openalex.org/W3115726904","https://openalex.org/W4241443503","https://openalex.org/W6654868677","https://openalex.org/W6670854576"],"related_works":["https://openalex.org/W590788508","https://openalex.org/W4235873430","https://openalex.org/W2611974471","https://openalex.org/W4313233093","https://openalex.org/W2358082531","https://openalex.org/W2589976903","https://openalex.org/W2335596023","https://openalex.org/W2392697706","https://openalex.org/W366033468","https://openalex.org/W2391054147"],"abstract_inverted_index":{"In":[0,35,161],"the":[1,17,32,44,57,67,93,97,104,120,127,137,164,172,184,188,192,199],"existing":[2,58],"high-order":[3,68,83,123,128],"fuzzy":[4,152],"logical":[5],"relationship":[6],"(FLR)":[7],"based":[8,155],"forecasting":[9,114,157,179,194],"model,":[10,163],"each":[11],"FLR":[12,71,86,95,132],"is":[13,72,133,159],"used":[14],"to":[15],"describe":[16],"association":[18,45,70,85,125,131,139,167],"between":[19,46],"multiple":[20,47,51,90,100,105],"premise":[21,48,101],"observations":[22,49,102],"and":[23,50,62,79,108,177,187],"a":[24,82,151],"consequent":[25,52,80,106],"observation.":[26],"Therefore,":[27],"these":[28,145],"FLRs":[29,59,168,186],"concentrate":[30],"on":[31,103],"one-step-ahead":[33],"forecasting.":[34],"real":[36],"applications,":[37],"there":[38],"exist":[39],"another":[40],"kind":[41],"of":[42,81,89,99,122,149,174,183,191],"association:":[43],"observations.":[53,91],"For":[54],"such":[55],"association,":[56],"can\u2019t":[60],"express":[61],"ignored.":[63],"To":[64],"depict":[65],"it,":[66],"multi-point":[69,84,124,129,165],"raised":[73],"in":[74,140,170],"this":[75,162],"study.":[76],"The":[77,181],"antecedent":[78],"are":[87,196],"consisted":[88],"Thus,":[92],"proposed":[94,185],"reflects":[96],"influence":[98],"observations,":[107],"can":[109],"be":[110],"applied":[111],"for":[112],"multi-step-ahead":[113,156],"with":[115],"no":[116],"cumulative":[117],"errors.":[118],"On":[119],"basis":[121],"FLR,":[126],"trend":[130,138],"constructed,":[134],"it":[135],"describes":[136],"time":[141,153,175],"series.":[142],"By":[143],"using":[144],"two":[146],"new":[147],"kinds":[148],"FLRs,":[150],"series":[154,176],"model":[158,195],"established.":[160],"(trend)":[166],"effective":[169],"capturing":[171],"associations":[173],"improving":[178],"accuracy.":[180],"benefits":[182],"superior":[189],"performance":[190],"established":[193],"demonstrated":[197],"through":[198],"experimental":[200],"analysis.":[201]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}