{"id":"https://openalex.org/W4396570313","doi":"https://doi.org/10.48550/arxiv.2404.16918","title":"On-the-fly Data Augmentation for Forecasting with Deep Learning","display_name":"On-the-fly Data Augmentation for Forecasting with Deep Learning","publication_year":2024,"publication_date":"2024-04-25","ids":{"openalex":"https://openalex.org/W4396570313","doi":"https://doi.org/10.48550/arxiv.2404.16918"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.16918","pdf_url":"http://arxiv.org/pdf/2404.16918","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2404.16918","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018859851","display_name":"V\u00edtor Cerqueira","orcid":"https://orcid.org/0000-0002-9694-8423"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cerqueira, Vitor","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101346990","display_name":"Mois\u00e9s Santos","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Santos, Mois\u00e9s","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019628800","display_name":"Yassine Baghoussi","orcid":"https://orcid.org/0000-0002-1943-1471"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baghoussi, Yassine","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068744113","display_name":"C. Guedes Soares","orcid":"https://orcid.org/0000-0002-8570-4263"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Soares, Carlos","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":77},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.735,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.735,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.7202,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.7105,"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/on-the-fly","display_name":"On the fly","score":0.62820673}],"concepts":[{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.62820673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5296264},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5087169},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4622848},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35044807},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32712355},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.16918","pdf_url":"http://arxiv.org/pdf/2404.16918","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.16918","pdf_url":"http://arxiv.org/pdf/2404.16918","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4306674287","https://openalex.org/W4285208911","https://openalex.org/W3215138031","https://openalex.org/W3082895349","https://openalex.org/W3046775127","https://openalex.org/W3009238340","https://openalex.org/W2961085424","https://openalex.org/W2731899572"],"abstract_inverted_index":{"Deep":[0],"learning":[1,156],"approaches":[2,57],"are":[3,39,204],"increasingly":[4],"used":[5],"to":[6,42,77,90,118,176],"tackle":[7],"forecasting":[8,145,157,178],"tasks.":[9],"A":[10],"key":[11],"factor":[12],"in":[13],"the":[14,44,114,134,139,149],"successful":[15],"application":[16],"of":[17,133,166],"these":[18,33,56],"methods":[19,92],"is":[20,28,48,116],"a":[21,53,59,95,107,119,130,153,164,181,192],"large":[22],"enough":[23],"training":[24,86,188],"sample":[25],"size,":[26],"which":[27,137],"not":[29,196],"always":[30],"available.":[31,206],"In":[32],"scenarios,":[34],"synthetic":[35],"data":[36,83,123,135,185,198],"generation":[37],"techniques":[38],"usually":[40],"applied":[41,50],"augment":[43],"dataset.":[45],"Data":[46,72],"augmentation":[47,84,103,186],"typically":[49],"before":[51,187],"fitting":[52],"model.":[54],"However,":[55],"create":[58,94],"single":[60],"augmented":[61,98,109,122],"dataset,":[62],"potentially":[63],"limiting":[64],"their":[65],"effectiveness.":[66],"This":[67],"work":[68],"introduces":[69],"OnDAT":[70,101,174],"(On-the-fly":[71],"Augmentation":[73],"for":[74,141],"Time":[75],"series)":[76],"address":[78],"this":[79,127],"issue":[80],"by":[81],"applying":[82],"during":[85],"and":[87,143,159,202],"validation.":[88],"Contrary":[89],"traditional":[91],"that":[93,173,183,194],"single,":[96],"static":[97],"dataset":[99,110],"beforehand,":[100],"performs":[102],"on-the-fly.":[104],"By":[105],"generating":[106],"new":[108],"on":[111],"each":[112],"iteration,":[113],"model":[115],"exposed":[117],"constantly":[120],"changing":[121],"variations.":[124],"We":[125,147],"hypothesize":[126],"process":[128],"enables":[129],"better":[131,177],"exploration":[132],"space,":[136],"reduces":[138],"potential":[140],"overfitting":[142],"improves":[144],"performance.":[146],"validated":[148],"proposed":[150],"approach":[151],"using":[152],"state-of-the-art":[154],"deep":[155],"method":[158,201],"8":[160],"benchmark":[161],"datasets":[162],"containing":[163],"total":[165],"75797":[167],"time":[168],"series.":[169],"The":[170,200],"experiments":[171,203],"suggest":[172],"leads":[175],"performance":[179],"than":[180],"strategy":[182,193],"applies":[184],"as":[189,191],"well":[190],"does":[195],"involve":[197],"augmentation.":[199],"publicly":[205]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4396570313","counts_by_year":[],"updated_date":"2025-04-18T17:43:13.638797","created_date":"2024-05-02"}