{"id":"https://openalex.org/W4391129999","doi":"https://doi.org/10.1109/access.2024.3357693","title":"Multi-Scale Transformer Pyramid Networks for Multivariate Time Series Forecasting","display_name":"Multi-Scale Transformer Pyramid Networks for Multivariate Time Series Forecasting","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4391129999","doi":"https://doi.org/10.1109/access.2024.3357693"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3357693","doi":"https://doi.org/10.1109/access.2024.3357693","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3357693","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10412052.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10412052.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102860798","display_name":"Yifan Zhang","orcid":"https://orcid.org/0000-0002-5832-2622","observed_orcids":["https://orcid.org/0000-0002-5832-2622"]},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Zhang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Nevada at Reno, Reno, NV, USA"],"raw_orcid":"https://orcid.org/0000-0002-5832-2622","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Nevada at Reno, Reno, NV, USA","institution_ids":["https://openalex.org/I134113660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082946134","display_name":"Rui Wu","orcid":"https://orcid.org/0000-0001-6134-5393","observed_orcids":["https://orcid.org/0000-0001-6134-5393"]},"institutions":[{"id":"https://openalex.org/I186335123","display_name":"East Carolina University","ror":"https://ror.org/01vx35703","country_code":"US","type":"education","lineage":["https://openalex.org/I186335123"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rui Wu","raw_affiliation_strings":["Department of Computer Science, East Carolina University, Greenville, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, East Carolina University, Greenville, NC, USA","institution_ids":["https://openalex.org/I186335123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002580372","display_name":"Sergiu M. Dascalu","orcid":"https://orcid.org/0000-0002-5485-1973","observed_orcids":["https://orcid.org/0000-0002-5485-1973"]},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergiu M. Dascalu","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Nevada at Reno, Reno, NV, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Nevada at Reno, Reno, NV, USA","institution_ids":["https://openalex.org/I134113660"]}]},{"author_position":"last","author":{"id":null,"display_name":"Frederick C. Harris","orcid":"https://orcid.org/0000-0002-0857-6931","observed_orcids":["https://orcid.org/0000-0002-0857-6931"]},"institutions":[{"id":"https://openalex.org/I134113660","display_name":"University of Nevada, Reno","ror":"https://ror.org/01keh0577","country_code":"US","type":"education","lineage":["https://openalex.org/I134113660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Frederick C. Harris","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Nevada at Reno, Reno, NV, USA"],"raw_orcid":"https://orcid.org/0000-0002-0857-6931","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Nevada at Reno, Reno, NV, USA","institution_ids":["https://openalex.org/I134113660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1995,"currency":"USD","value_usd":1995},"apc_paid":{"value":1995,"currency":"USD","value_usd":1995},"fwci":9.183,"has_fulltext":true,"cited_by_count":52,"citation_normalized_percentile":{"value":0.98801128,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"12","issue":null,"first_page":"14731","last_page":"14741"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994999766349792,"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":0.9994999766349792,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.0003000000142492354,"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":9.999999747378752e-05,"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/multivariate-time-series-forecasting","display_name":"multivariate time series forecasting","score":1.0},{"id":"https://openalex.org/keywords/multi-scale-transformer","display_name":"multi-scale transformer","score":0.7039999961853027},{"id":"https://openalex.org/keywords/temporal-dependencies","display_name":"temporal dependencies","score":0.6779999732971191},{"id":"https://openalex.org/keywords/seasonal-variation","display_name":"seasonal variation","score":0.625}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067750096321106},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5964418649673462},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5582651495933533},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4964800477027893},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.48941770195961},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.46897825598716736},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4520905911922455},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4283660352230072},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4250292479991913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3637799620628357},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34095776081085205},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12441781163215637},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/access.2024.3357693","doi":"https://doi.org/10.1109/access.2024.3357693","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3357693","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10412052.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2308.11946","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2308.11946","pdf_url":"https://arxiv.org/pdf/2308.11946","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:669ecc530da4496e88b22ce6416ae61f","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/669ecc530da4496e88b22ce6416ae61f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 14731-14741 (2024)","raw_type":"article"},{"id":"doi:10.48550/arxiv.2308.11946","doi":"https://doi.org/10.48550/arxiv.2308.11946","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2308.11946","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3357693","doi":"https://doi.org/10.1109/access.2024.3357693","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3357693","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10412052.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2099105876","display_name":"Collaborative Research: A Student-Centered Personalized Learning Framework to Advance Undergraduate Robotics Education","funder_award_id":"2142428","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5309336706","display_name":"RII Track-1: Harnessing the Data Revolution for Fire Science","funder_award_id":"2148788","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6405410461","display_name":"RII Track-2 FEC: Leveraging Big Data to Improve Prediction of Tick-Borne Disease Patterns and Dynamics","funder_award_id":"2019609","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8179720856","display_name":null,"funder_award_id":"OIA-2148,788","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8588099119","display_name":"Collaborative Research: A Student-Centered Personalized Learning Framework to Advance Undergraduate Robotics Education","funder_award_id":"2142360","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391129999.pdf","grobid_xml":"https://content.openalex.org/works/W4391129999.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2500779354","https://openalex.org/W2565639579","https://openalex.org/W2604847698","https://openalex.org/W2626778328","https://openalex.org/W2770058355","https://openalex.org/W2797846142","https://openalex.org/W2890096158","https://openalex.org/W3037932933","https://openalex.org/W3080253043","https://openalex.org/W3131500599","https://openalex.org/W3173539742","https://openalex.org/W3177318507","https://openalex.org/W4205650351","https://openalex.org/W4225494949","https://openalex.org/W4376608362","https://openalex.org/W4382203079","https://openalex.org/W4385763767","https://openalex.org/W4386385376","https://openalex.org/W6846825190","https://openalex.org/W6889955440","https://openalex.org/W7133205715"],"related_works":["https://openalex.org/W4416290715","https://openalex.org/W7131294723","https://openalex.org/W4412609342","https://openalex.org/W4415709060","https://openalex.org/W4388430464","https://openalex.org/W4416017550","https://openalex.org/W7160406329","https://openalex.org/W7117308696","https://openalex.org/W4416252285","https://openalex.org/W4413263894"],"abstract_inverted_index":{"Multivariate":[0],"Time":[1],"Series":[2],"(MTS)":[3],"forecasting":[4,24],"entails":[5],"the":[6,94,144,195],"intricate":[7],"process":[8],"of":[9,174],"modeling":[10,40],"temporal":[11,41,81,115,175],"dependencies":[12,42,116],"within":[13],"historical":[14],"data":[15,87,192],"records.":[16],"Transformers":[17],"have":[18],"demonstrated":[19],"remarkable":[20],"performance":[21,154],"in":[22,153,158,161,189],"MTS":[23,86,191],"due":[25],"to":[26,29,39,63,78,113,168,180],"their":[27,61],"capability":[28],"capture":[30,65,79,114,170],"long-term":[31],"dependencies.":[32,82],"However,":[33],"prior":[34],"work":[35],"has":[36],"been":[37],"confined":[38],"at":[43,117,133,194],"either":[44],"a":[45,73,89,104,171],"fixed":[46],"scale":[47],"or":[48],"multiple":[49,118],"scales":[50,120],"that":[51,143],"exponentially":[52],"increase":[53],"(most":[54],"with":[55],"base":[56],"2).":[57],"This":[58,83,151,183],"limitation":[59],"impedes":[60],"capacity":[62],"effectively":[64,169],"diverse":[66],"seasonalities.":[67],"In":[68],"our":[69],"study,":[70],"we":[71,102],"present":[72,103],"dimension-invariant":[74],"embedding":[75],"technique":[76],"designed":[77,112],"short-term":[80],"procedure":[84],"projects":[85],"into":[88],"higher-dimensional":[90],"space":[91],"while":[92],"preserving":[93],"original":[95],"time":[96],"steps":[97],"and":[98],"variable":[99],"dimensions.":[100],"Furthermore,":[101],"novel":[105],"Multi-scale":[106],"Transformer":[107],"Pyramid":[108],"Network":[109],"(MTPNet),":[110],"specifically":[111],"unconstrained":[119],"effectively.":[121],"The":[122],"predictions":[123],"are":[124],"inferred":[125],"from":[126,131,178],"multi-scale":[127],"latent":[128],"representations":[129],"obtained":[130],"transformers":[132],"various":[134],"scales.":[135,182],"Extensive":[136],"experiments":[137],"on":[138],"nine":[139],"benchmark":[140],"datasets":[141,159],"demonstrate":[142],"proposed":[145],"MTPNet":[146,167],"outperforms":[147],"recent":[148],"state-of-the-art":[149],"methods.":[150],"enhancement":[152],"is":[155],"particularly":[156],"pronounced":[157],"rich":[160],"fine-scale":[162],"information,":[163],"as":[164],"it":[165],"enables":[166],"wide":[172],"spectrum":[173],"dependencies,":[176],"ranging":[177],"fine":[179],"coarse":[181],"finding":[184],"highlights":[185],"MTPNet\u2019s":[186],"notable":[187],"potential":[188],"analyzing":[190],"sampled":[193],"minute":[196],"level.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":26},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2024-01-24T00:00:00"}