{"id":"https://openalex.org/W4312564419","doi":"https://doi.org/10.1587/transfun.2022eap1081","title":"Time-Series Prediction Based on Double Pyramid Bidirectional Feature Fusion Mechanism","display_name":"Time-Series Prediction Based on Double Pyramid Bidirectional Feature Fusion Mechanism","publication_year":2022,"publication_date":"2022-12-19","ids":{"openalex":"https://openalex.org/W4312564419","doi":"https://doi.org/10.1587/transfun.2022eap1081"},"language":"en","primary_location":{"id":"doi:10.1587/transfun.2022eap1081","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transfun.2022eap1081","pdf_url":"https://www.jstage.jst.go.jp/article/transfun/E106.A/6/E106.A_2022EAP1081/_pdf","source":{"id":"https://openalex.org/S166990724","display_name":"IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences","issn_l":"0916-8508","issn":["0916-8508","1745-1337"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.jstage.jst.go.jp/article/transfun/E106.A/6/E106.A_2022EAP1081/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035713786","display_name":"Na WANG","orcid":null},"institutions":[{"id":"https://openalex.org/I206777745","display_name":"Nanjing Audit University","ror":"https://ror.org/04zj2bd87","country_code":"CN","type":"education","lineage":["https://openalex.org/I206777745"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na WANG","raw_affiliation_strings":["College of Economics and Management, Nanjing University of Aeronautics and Astronautics","Department of Accounting and Audit, Nanjing Audit University Jinshen College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Economics and Management, Nanjing University of Aeronautics and Astronautics","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"Department of Accounting and Audit, Nanjing Audit University Jinshen College","institution_ids":["https://openalex.org/I206777745"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029732484","display_name":"Xianglian ZHAO","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianglian ZHAO","raw_affiliation_strings":["College of Economics and Management, Nanjing University of Aeronautics and Astronautics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Economics and Management, Nanjing University of Aeronautics and Astronautics","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2828,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.50827902,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"E106.A","issue":"6","first_page":"886","last_page":"895"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9983000159263611,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7467548251152039},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5453675389289856},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5219444632530212},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4984157085418701},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4339732825756073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42795252799987793},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42439427971839905},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3935912251472473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3560265302658081},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2539307475090027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7467548251152039},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5453675389289856},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5219444632530212},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4984157085418701},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4339732825756073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42795252799987793},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42439427971839905},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3935912251472473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3560265302658081},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2539307475090027},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transfun.2022eap1081","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transfun.2022eap1081","pdf_url":"https://www.jstage.jst.go.jp/article/transfun/E106.A/6/E106.A_2022EAP1081/_pdf","source":{"id":"https://openalex.org/S166990724","display_name":"IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences","issn_l":"0916-8508","issn":["0916-8508","1745-1337"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transfun.2022eap1081","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transfun.2022eap1081","pdf_url":"https://www.jstage.jst.go.jp/article/transfun/E106.A/6/E106.A_2022EAP1081/_pdf","source":{"id":"https://openalex.org/S166990724","display_name":"IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences","issn_l":"0916-8508","issn":["0916-8508","1745-1337"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312564419.pdf","grobid_xml":"https://content.openalex.org/works/W4312564419.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1484842423","https://openalex.org/W1810943226","https://openalex.org/W1815076433","https://openalex.org/W2064675550","https://openalex.org/W2111440106","https://openalex.org/W2130942839","https://openalex.org/W2136922672","https://openalex.org/W2168950978","https://openalex.org/W2172140247","https://openalex.org/W2413794162","https://openalex.org/W2546191734","https://openalex.org/W2604847698","https://openalex.org/W2607045400","https://openalex.org/W2756203131","https://openalex.org/W2765932895","https://openalex.org/W2792764867","https://openalex.org/W2797846142","https://openalex.org/W2889928394","https://openalex.org/W2896457183","https://openalex.org/W2902854273","https://openalex.org/W2954731415","https://openalex.org/W2963951265","https://openalex.org/W3004608407","https://openalex.org/W3030163527","https://openalex.org/W3094502228","https://openalex.org/W3097294131","https://openalex.org/W3103720336","https://openalex.org/W3138516171","https://openalex.org/W3177318507","https://openalex.org/W3194203264","https://openalex.org/W4239185196"],"related_works":["https://openalex.org/W1657880117","https://openalex.org/W2595172197","https://openalex.org/W2127970246","https://openalex.org/W2084856301","https://openalex.org/W1001352512","https://openalex.org/W2622688551","https://openalex.org/W2119012848","https://openalex.org/W1990205660","https://openalex.org/W1550175370","https://openalex.org/W4387331850"],"abstract_inverted_index":{"The":[0,108],"application":[1],"of":[2,65,111,123],"time-series":[3,81,125,141],"prediction":[4,25,63,192],"is":[5,10,91,144],"very":[6],"extensive,":[7],"and":[8,23,26,36,53,159],"it":[9,74,185],"an":[11,136],"important":[12],"problem":[13],"across":[14],"many":[15],"fields,":[16],"such":[17,83],"as":[18],"stock":[19],"prediction,":[20,22,82],"sales":[21],"loan":[24],"so":[27],"on,":[28],"which":[29,98],"play":[30],"a":[31,145],"great":[32],"value":[33],"in":[34,89,103],"production":[35],"life.":[37],"It":[38,143],"requires":[39],"that":[40,58,72],"the":[41,46,51,62,117,166,173,178,189],"model":[42,101,138],"can":[43,60,164,186],"effectively":[44],"capture":[45],"long-term":[47],"feature":[48,96,149],"dependence":[49],"between":[50],"output":[52],"input.":[54],"Recent":[55],"studies":[56],"show":[57],"Transformer":[59,68,90],"improve":[61],"ability":[64],"time-series.":[66],"However,":[67],"has":[69],"some":[70],"problems":[71],"make":[73],"unable":[75],"to":[76,80,94,100,129],"be":[77],"directly":[78],"applied":[79],"as:":[84],"(1)":[85],"Local":[86],"agnosticism:":[87],"Self-attention":[88],"not":[92],"sensitive":[93],"short-term":[95],"dependence,":[97],"leads":[99],"anomalies":[102],"time-series;":[104],"(2)":[105],"Memory":[106],"bottleneck:":[107],"spatial":[109],"complexity":[110],"regular":[112],"transformation":[113],"increases":[114],"twice":[115],"with":[116,153,177],"sequence":[118],"length,":[119],"making":[120],"direct":[121],"modeling":[122],"long":[124,140],"infeasible.":[126],"In":[127],"order":[128],"solve":[130],"these":[131],"problems,":[132],"this":[133],"paper":[134],"designs":[135],"efficient":[137],"for":[139],"prediction.":[142],"double":[146],"pyramid":[147],"bidirectional":[148],"fusion":[150],"mechanism":[151],"network":[152,162],"parallel":[154],"Temporal":[155,174],"Convolution":[156,175],"Network":[157,176],"(TCN)":[158],"FastFormer.":[160],"This":[161],"structure":[163],"combine":[165],"time":[167,190],"series":[168,191],"fine-grained":[169],"information":[170,181],"captured":[171,182],"by":[172,183],"global":[179],"interactive":[180],"FastFormer,":[184],"well":[187],"handle":[188],"problem.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}