{"id":"https://openalex.org/W4396954949","doi":"https://doi.org/10.3390/bdcc8050048","title":"Enhanced Linear and Vision Transformer-Based Architectures for Time Series Forecasting","display_name":"Enhanced Linear and Vision Transformer-Based Architectures for Time Series Forecasting","publication_year":2024,"publication_date":"2024-05-16","ids":{"openalex":"https://openalex.org/W4396954949","doi":"https://doi.org/10.3390/bdcc8050048"},"language":"en","primary_location":{"id":"doi:10.3390/bdcc8050048","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8050048","pdf_url":"https://www.mdpi.com/2504-2289/8/5/48/pdf?version=1715855564","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-2289/8/5/48/pdf?version=1715855564","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5095770807","display_name":"Musleh Alharthi","orcid":null},"institutions":[{"id":"https://openalex.org/I154300980","display_name":"University of Bridgeport","ror":"https://ror.org/01rf3yp57","country_code":"US","type":"education","lineage":["https://openalex.org/I154300980"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Musleh Alharthi","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT 06604, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT 06604, USA","institution_ids":["https://openalex.org/I154300980"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005346248","display_name":"Ausif Mahmood","orcid":"https://orcid.org/0000-0002-8991-4268"},"institutions":[{"id":"https://openalex.org/I154300980","display_name":"University of Bridgeport","ror":"https://ror.org/01rf3yp57","country_code":"US","type":"education","lineage":["https://openalex.org/I154300980"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ausif Mahmood","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT 06604, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT 06604, USA","institution_ids":["https://openalex.org/I154300980"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5095770807"],"corresponding_institution_ids":["https://openalex.org/I154300980"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.8677,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.8545805,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"8","issue":"5","first_page":"48","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9976000189781189,"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":0.989300012588501,"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/computer-science","display_name":"Computer science","score":0.7192813754081726},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6930562257766724},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6406035423278809},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6009119749069214},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.578851580619812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5229440331459045},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5154067277908325},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4969334900379181},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42308321595191956},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1780242621898651},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.14746356010437012},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09717229008674622},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.08125177025794983}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7192813754081726},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6930562257766724},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6406035423278809},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6009119749069214},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.578851580619812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5229440331459045},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5154067277908325},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4969334900379181},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42308321595191956},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1780242621898651},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.14746356010437012},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09717229008674622},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.08125177025794983},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/bdcc8050048","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8050048","pdf_url":"https://www.mdpi.com/2504-2289/8/5/48/pdf?version=1715855564","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e0f1a9f5729145c9b16174199ae7945c","is_oa":true,"landing_page_url":"https://doaj.org/article/e0f1a9f5729145c9b16174199ae7945c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data and Cognitive Computing, Vol 8, Iss 5, p 48 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/bdcc8050048","is_oa":true,"landing_page_url":"https://doi.org/10.3390/bdcc8050048","pdf_url":"https://www.mdpi.com/2504-2289/8/5/48/pdf?version=1715855564","source":{"id":"https://openalex.org/S4210238752","display_name":"Big Data and Cognitive Computing","issn_l":"2504-2289","issn":["2504-2289"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data and Cognitive Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396954949.pdf"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W2109316012","https://openalex.org/W2604847698","https://openalex.org/W2971724044","https://openalex.org/W2980994438","https://openalex.org/W3020866103","https://openalex.org/W3022643593","https://openalex.org/W3132782787","https://openalex.org/W3138516171","https://openalex.org/W3177318507","https://openalex.org/W4225494949","https://openalex.org/W4382203079","https://openalex.org/W4403488223","https://openalex.org/W6786852218","https://openalex.org/W6849157316","https://openalex.org/W6889955440"],"related_works":["https://openalex.org/W2591697403","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2359348847","https://openalex.org/W3011538607","https://openalex.org/W2171218219","https://openalex.org/W4294432981","https://openalex.org/W4321441197","https://openalex.org/W1972271943","https://openalex.org/W2349019353"],"abstract_inverted_index":{"Time":[0],"series":[1,37,66,145],"forecasting":[2,38,146],"has":[3],"been":[4,32,44],"a":[5,101,108,148],"challenging":[6],"area":[7],"in":[8,46,53,63,87],"the":[9,35,47,57,64,90,117,151],"field":[10],"of":[11,111,150],"Artificial":[12],"Intelligence.":[13],"Various":[14],"approaches":[15],"such":[16],"as":[17],"linear":[18,22,78,91,121],"neural":[19,23,92,122],"networks,":[20,24],"recurrent":[21],"Convolutional":[25],"Neural":[26],"Networks,":[27],"and":[28,94,132],"recently":[29,118],"transformers":[30,62],"have":[31,43,68],"attempted":[33],"for":[34,107,143],"time":[36,65,144],"domain.":[39],"Although":[40],"transformer-based":[41,81,95],"architectures":[42,142],"outstanding":[45],"Natural":[48],"Language":[49],"Processing":[50],"domain,":[51],"especially":[52],"autoregressive":[54],"language":[55],"modeling,":[56],"initial":[58],"attempts":[59],"to":[60],"use":[61],"arena":[67],"met":[69],"mixed":[70],"success.":[71],"A":[72],"recent":[73],"important":[74],"work":[75],"indicating":[76],"simple":[77,120],"networks":[79],"outperform":[80],"designs.":[82],"We":[83,113],"investigate":[84],"this":[85],"paradox":[86],"detail":[88],"comparing":[89],"network-":[93],"designs,":[96],"providing":[97],"insights":[98],"into":[99],"why":[100],"certain":[102],"approach":[103],"may":[104],"be":[105],"better":[106],"particular":[109],"type":[110],"problem.":[112],"also":[114],"improve":[115],"upon":[116],"proposed":[119],"network-based":[123],"architecture":[124,138],"by":[125],"using":[126],"dual":[127],"pipelines":[128],"with":[129],"batch":[130],"normalization":[131],"reversible":[133],"instance":[134],"normalization.":[135],"Our":[136],"enhanced":[137],"outperforms":[139],"all":[140],"existing":[141],"on":[147],"majority":[149],"popular":[152],"benchmarks.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
