{"id":"https://openalex.org/W3088460416","doi":"https://doi.org/10.1108/gs-05-2020-0069","title":"Analysing and forecasting China containerized freight index with a hybrid decomposition\u2013ensemble method based on EMD, grey wave and ARMA","display_name":"Analysing and forecasting China containerized freight index with a hybrid decomposition\u2013ensemble method based on EMD, grey wave and ARMA","publication_year":2020,"publication_date":"2020-09-22","ids":{"openalex":"https://openalex.org/W3088460416","doi":"https://doi.org/10.1108/gs-05-2020-0069","mag":"3088460416"},"language":"en","primary_location":{"id":"doi:10.1108/gs-05-2020-0069","is_oa":false,"landing_page_url":"https://doi.org/10.1108/gs-05-2020-0069","pdf_url":null,"source":{"id":"https://openalex.org/S4210188239","display_name":"Grey Systems Theory and Application","issn_l":"2043-9377","issn":["2043-9377","2043-9385"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Grey Systems: Theory and Application","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/A5086370451","display_name":"Yanhui Chen","orcid":"https://orcid.org/0000-0003-1091-2786"},"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":"Yanhui Chen","raw_affiliation_strings":["School of Economics and Management, Shanghai Maritime University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1091-2786","affiliations":[{"raw_affiliation_string":"School of Economics and Management, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100334256","display_name":"Bin Liu","orcid":"https://orcid.org/0000-0002-9443-8489"},"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":"Bin Liu","raw_affiliation_strings":["School of Economics and Management, Shanghai Maritime University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106407750","display_name":"Tianzi Wang","orcid":"https://orcid.org/0009-0005-5823-3039"},"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":"Tianzi Wang","raw_affiliation_strings":["School of Economics and Management, Shanghai Maritime University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086370451"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":null,"apc_paid":null,"fwci":1.6728,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.85675104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":"3","first_page":"358","last_page":"371"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.9958000183105469,"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/T12368","display_name":"Grey System Theory Applications","score":0.9958000183105469,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9520999789237976,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8675176501274109},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4927068054676056},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4802980124950409},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4475020170211792},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4345815181732178},{"id":"https://openalex.org/keywords/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.43285080790519714},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.43124523758888245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.340759813785553},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3369556963443756},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3226660490036011},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32130175828933716},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3204384446144104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22963255643844604},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.17172697186470032},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.14564165472984314}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8675176501274109},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4927068054676056},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4802980124950409},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4475020170211792},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4345815181732178},{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.43285080790519714},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.43124523758888245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.340759813785553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3369556963443756},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3226660490036011},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32130175828933716},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3204384446144104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22963255643844604},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.17172697186470032},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.14564165472984314}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/gs-05-2020-0069","is_oa":false,"landing_page_url":"https://doi.org/10.1108/gs-05-2020-0069","pdf_url":null,"source":{"id":"https://openalex.org/S4210188239","display_name":"Grey Systems Theory and Application","issn_l":"2043-9377","issn":["2043-9377","2043-9385"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Grey Systems: Theory and Application","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.44999998807907104,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1661370443","https://openalex.org/W1966938154","https://openalex.org/W1981271277","https://openalex.org/W1987756433","https://openalex.org/W1989102338","https://openalex.org/W1995059421","https://openalex.org/W2007221293","https://openalex.org/W2014683958","https://openalex.org/W2016881509","https://openalex.org/W2018037073","https://openalex.org/W2022885136","https://openalex.org/W2026569503","https://openalex.org/W2028702910","https://openalex.org/W2031340629","https://openalex.org/W2042972495","https://openalex.org/W2063530343","https://openalex.org/W2064649121","https://openalex.org/W2085987121","https://openalex.org/W2086840572","https://openalex.org/W2091950080","https://openalex.org/W2093311990","https://openalex.org/W2098395403","https://openalex.org/W2106665847","https://openalex.org/W2133773734","https://openalex.org/W2140208140","https://openalex.org/W2220779474","https://openalex.org/W2340541161","https://openalex.org/W2494297716","https://openalex.org/W2592669101","https://openalex.org/W2792836263","https://openalex.org/W2795348462","https://openalex.org/W2897669153","https://openalex.org/W2900794547"],"related_works":["https://openalex.org/W2081563414","https://openalex.org/W2363056446","https://openalex.org/W2359718298","https://openalex.org/W1915398038","https://openalex.org/W2185837235","https://openalex.org/W3097417252","https://openalex.org/W1989764538","https://openalex.org/W2021955905","https://openalex.org/W3115491726","https://openalex.org/W2380210200"],"abstract_inverted_index":{"Purpose":[0],"This":[1,23],"paper":[2],"applied":[3,125],"grey":[4,31,55,94,160,170],"wave":[5,32,56,95,161,178],"forecasting":[6,10,33,96,162,175,179],"in":[7,19,35,75,126,149,192,196],"a":[8],"decomposition\u2013ensemble":[9,44,154],"method":[11,34,45,141,155],"for":[12,89,182],"modelling":[13],"the":[14,28,76,82,93,108,115,118,135,139,165,169,193],"complex":[15],"and":[16,54,81,147,159,173],"non-linear":[17],"features":[18],"time":[20,37,65,133],"series":[21,38,66],"data.":[22],"application":[24,166],"aims":[25],"to":[26,63,102,107],"test":[27],"advantages":[29],"of":[30,84,110,168],"predicting":[36],"with":[39,185],"periodic":[40,186],"fluctuations.":[41,187],"Design/methodology/approach":[42],"The":[43,153],"combines":[46],"empirical":[47,116],"mode":[48,71],"decomposition":[49],"(EMD),":[50],"component":[51,90],"reconstruction":[52],"technology":[53],"forecasting.":[57],"More":[58],"specifically,":[59],"EMD":[60,158],"is":[61,100,124],"used":[62,101],"decompose":[64],"data":[67,183],"into":[68],"different":[69,132],"intrinsic":[70],"function":[72],"(IMF)":[73],"components":[74],"first":[77],"step.":[78],"Permutation":[79],"entropy":[80],"average":[83],"each":[85,104,111],"IMF":[86,105],"are":[87],"checked":[88],"reconstruction.":[91],"Then":[92],"model":[97,163],"or":[98],"ARMA":[99,148],"predict":[103],"according":[106],"characters":[109],"IMF.":[112],"Findings":[113],"In":[114],"analysis,":[117],"China":[119],"container":[120],"freight":[121],"index":[122],"(CCFI)":[123],"checking":[127],"prediction":[128],"performance.":[129],"Using":[130],"two":[131],"periods,":[134],"results":[136],"show":[137],"that":[138],"proposed":[140],"performs":[142,180],"better":[143,181],"than":[144],"random":[145],"walk":[146],"multi-step-ahead":[150],"prediction.":[151],"Originality/value":[152],"based":[156],"on":[157],"expands":[164],"area":[167],"system":[171],"theory":[172],"graphic":[174],"method.":[176],"Grey":[177],"set":[184],"Forecasting":[188],"CCFI":[189],"assists":[190],"practitioners":[191],"shipping":[194],"industry":[195],"decision-making.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3}],"updated_date":"2026-05-13T08:25:38.343686","created_date":"2025-10-10T00:00:00"}