{"id":"https://openalex.org/W2052186264","doi":"https://doi.org/10.4018/jkss.2012040105","title":"A Hybrid Forecasting Model for Non-Stationary Time Series","display_name":"A Hybrid Forecasting Model for Non-Stationary Time Series","publication_year":2012,"publication_date":"2012-04-01","ids":{"openalex":"https://openalex.org/W2052186264","doi":"https://doi.org/10.4018/jkss.2012040105","mag":"2052186264"},"language":"en","primary_location":{"id":"doi:10.4018/jkss.2012040105","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jkss.2012040105","pdf_url":null,"source":{"id":"https://openalex.org/S200968236","display_name":"International Journal of Knowledge and Systems Science","issn_l":"1947-8208","issn":["1947-8208","1947-8216"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Knowledge and Systems Science","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/A5103085812","display_name":"Yi Xiao","orcid":"https://orcid.org/0000-0002-0781-5777"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Xiao","raw_affiliation_strings":["Central China Normal University and Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Central China Normal University and Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068860197","display_name":"Jin Xiao","orcid":"https://orcid.org/0000-0002-9369-6267"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Xiao","raw_affiliation_strings":["Sichuan University and Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Sichuan University and Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111758530","display_name":"Shouyang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouyang Wang","raw_affiliation_strings":["Chinese Academy of Sciences, China","Chinese academy of sciences, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese academy of sciences, China#TAB#","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103085812"],"corresponding_institution_ids":["https://openalex.org/I40963666"],"apc_list":null,"apc_paid":null,"fwci":3.9988,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.93495652,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"3","issue":"2","first_page":"67","last_page":"82"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9962000250816345,"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/T10320","display_name":"Neural Networks and Applications","score":0.9955000281333923,"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":0.7202200889587402},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6640390157699585},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.6615403294563293},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5484174489974976},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5406098365783691},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5164070725440979},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.47701287269592285},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.46575266122817993},{"id":"https://openalex.org/keywords/mutation","display_name":"Mutation","score":0.46184343099594116},{"id":"https://openalex.org/keywords/inertia","display_name":"Inertia","score":0.436027467250824},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.39937326312065125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33902406692504883},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2839626669883728},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1387057602405548}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7202200889587402},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6640390157699585},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.6615403294563293},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5484174489974976},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5406098365783691},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5164070725440979},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.47701287269592285},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.46575266122817993},{"id":"https://openalex.org/C501734568","wikidata":"https://www.wikidata.org/wiki/Q42918","display_name":"Mutation","level":3,"score":0.46184343099594116},{"id":"https://openalex.org/C110407247","wikidata":"https://www.wikidata.org/wiki/Q122508","display_name":"Inertia","level":2,"score":0.436027467250824},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.39937326312065125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33902406692504883},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2839626669883728},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1387057602405548},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/jkss.2012040105","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jkss.2012040105","pdf_url":null,"source":{"id":"https://openalex.org/S200968236","display_name":"International Journal of Knowledge and Systems Science","issn_l":"1947-8208","issn":["1947-8208","1947-8216"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Knowledge and Systems Science","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jkss00:v:3:y:2012:i:2:p:67-82","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jkss.2012040105","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W625457988","https://openalex.org/W1576426930","https://openalex.org/W1811781384","https://openalex.org/W1969681270","https://openalex.org/W1975994995","https://openalex.org/W1978740922","https://openalex.org/W1983438816","https://openalex.org/W1995341919","https://openalex.org/W2000691296","https://openalex.org/W2018672055","https://openalex.org/W2021083107","https://openalex.org/W2021309800","https://openalex.org/W2025179714","https://openalex.org/W2028569720","https://openalex.org/W2044280558","https://openalex.org/W2053865013","https://openalex.org/W2058974375","https://openalex.org/W2062238863","https://openalex.org/W2073807441","https://openalex.org/W2092436092","https://openalex.org/W2095364399","https://openalex.org/W2108388069","https://openalex.org/W2108537597","https://openalex.org/W2108959409","https://openalex.org/W2117014758","https://openalex.org/W2127277876","https://openalex.org/W2129986954","https://openalex.org/W2131613989","https://openalex.org/W2137983211","https://openalex.org/W2152503192","https://openalex.org/W2161201021","https://openalex.org/W2166843422","https://openalex.org/W2350419976","https://openalex.org/W3146803896","https://openalex.org/W4230644069"],"related_works":["https://openalex.org/W1982679530","https://openalex.org/W3111286355","https://openalex.org/W4285212364","https://openalex.org/W2360100473","https://openalex.org/W2147124600","https://openalex.org/W2115729582","https://openalex.org/W2114356839","https://openalex.org/W2363406585","https://openalex.org/W3134384462","https://openalex.org/W2125094050"],"abstract_inverted_index":{"In":[0,28,62],"time":[1],"series":[2],"analysis,":[3],"an":[4,89,103,141],"important":[5],"problem":[6],"is":[7,46,68],"how":[8],"to":[9,72],"extract":[10],"the":[11,15,31,50,63,73,127,135,148,159],"information":[12],"hidden":[13],"in":[14],"non-stationary":[16],"and":[17,20,79,88,102,121,140],"noise":[18],"data":[19],"combine":[21],"it":[22],"into":[23],"a":[24,34,85,94],"model":[25],"for":[26,60],"forecasting.":[27,61],"this":[29],"paper,":[30],"authors":[32],"propose":[33],"TEI@I":[35],"based":[36,48,107],"hybrid":[37],"forecasting":[38],"model.":[39],"A":[40],"novel":[41],"feed":[42],"forward":[43],"neural":[44],"network":[45],"developed":[47],"on":[49,100,108,147],"improved":[51],"particle":[52,123],"swarm":[53,124],"optimization":[54],"with":[55,134,158],"adaptive":[56,104],"genetic":[57],"operator":[58],"(IPSO-FNN)":[59],"proposed":[64,160],"IPSO,":[65],"inertia":[66],"weight":[67],"dynamically":[69],"adjusted":[70,133],"according":[71],"feedback":[74],"from":[75,137],"particles\u2019":[76],"best":[77],"memories,":[78],"acceleration":[80],"coefficients":[81],"are":[82,111,117,132,162],"controlled":[83],"by":[84,119],"declining":[86],"arccosine":[87,91],"increasing":[90],"function.":[92],"Subsequently,":[93],"crossover":[95],"rate":[96,106],"which":[97],"only":[98],"depends":[99],"generation":[101],"mutation":[105],"individual":[109],"fitness":[110],"designed.":[112],"The":[113,144],"parameters":[114],"of":[115,130,152],"FNN":[116],"optimized":[118],"binary":[120],"decimal":[122],"optimization.":[125],"Further,":[126],"forecast":[128,151],"results":[129,146],"IPSO-FNN":[131],"knowledge":[136],"text":[138],"mining":[139],"expert":[142],"system.":[143],"empirical":[145],"container":[149],"throughput":[150],"Tianjin":[153],"Port":[154],"show":[155],"that":[156],"forecasts":[157],"method":[161],"much":[163],"better":[164],"than":[165],"some":[166],"other":[167],"methods.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}
