{"id":"https://openalex.org/W4399356181","doi":"https://doi.org/10.3389/fdata.2024.1376023","title":"Unilateral boundary time series forecasting","display_name":"Unilateral boundary time series forecasting","publication_year":2024,"publication_date":"2024-06-05","ids":{"openalex":"https://openalex.org/W4399356181","doi":"https://doi.org/10.3389/fdata.2024.1376023","pmid":"https://pubmed.ncbi.nlm.nih.gov/38903951"},"language":"en","primary_location":{"id":"doi:10.3389/fdata.2024.1376023","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1376023","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2024.1376023/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/fdata.2024.1376023/pdf?isPublishedV2=False","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102682285","display_name":"Chao-Min Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chao-Min Chang","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014600496","display_name":"Cheng\u2013Te Li","orcid":"https://orcid.org/0000-0001-7995-4787"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Cheng-Te Li","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087480257","display_name":"Shou-De Lin","orcid":"https://orcid.org/0000-0001-9970-1250"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shou-De Lin","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014600496"],"corresponding_institution_ids":["https://openalex.org/I91807558"],"apc_list":{"value":1285,"currency":"USD","value_usd":1285},"apc_paid":{"value":1285,"currency":"USD","value_usd":1285},"fwci":1.0606,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.74426934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"1376023","last_page":"1376023"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9980000257492065,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.996999979019165,"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":0.707085371017456},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6917926669120789},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5524121522903442},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4841924011707306},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4783432185649872},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4434947371482849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39314472675323486},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.35092341899871826},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12948310375213623}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.707085371017456},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6917926669120789},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5524121522903442},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4841924011707306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4783432185649872},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4434947371482849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39314472675323486},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.35092341899871826},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12948310375213623},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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":4,"locations":[{"id":"doi:10.3389/fdata.2024.1376023","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1376023","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2024.1376023/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},{"id":"pmid:38903951","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38903951","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in big data","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11188450","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11188450","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11188450/pdf/fdata-07-1376023.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Front Big Data","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:9182265dace44e298c1e6d37d71173c3","is_oa":false,"landing_page_url":"https://doaj.org/article/9182265dace44e298c1e6d37d71173c3","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,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Big Data, Vol 7 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fdata.2024.1376023","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fdata.2024.1376023","pdf_url":"https://www.frontiersin.org/articles/10.3389/fdata.2024.1376023/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210201220","display_name":"Frontiers in Big Data","issn_l":"2624-909X","issn":["2624-909X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321041","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784"},{"id":"https://openalex.org/F4320323900","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95"},{"id":"https://openalex.org/F4320324663","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49"},{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399356181.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1977142024","https://openalex.org/W2025700125","https://openalex.org/W2036820974","https://openalex.org/W2154326182","https://openalex.org/W2157331557","https://openalex.org/W2489782956","https://openalex.org/W2604847698","https://openalex.org/W2612690371","https://openalex.org/W2801959627","https://openalex.org/W2808766921","https://openalex.org/W2964010366","https://openalex.org/W2997292607","https://openalex.org/W3080157892","https://openalex.org/W4225987319","https://openalex.org/W4283807683","https://openalex.org/W4306884390","https://openalex.org/W4316039505","https://openalex.org/W4360995171","https://openalex.org/W4377710500","https://openalex.org/W4382239131","https://openalex.org/W4382239660","https://openalex.org/W4385245566","https://openalex.org/W4387929543","https://openalex.org/W4393965942","https://openalex.org/W6739901393","https://openalex.org/W6745609711","https://openalex.org/W6810424057","https://openalex.org/W6839232038","https://openalex.org/W6846376059","https://openalex.org/W6855650930","https://openalex.org/W6856867528"],"related_works":["https://openalex.org/W2770593030","https://openalex.org/W3154990682","https://openalex.org/W1919101720","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W2377538627","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Time":[0],"series":[1,41,212],"forecasting":[2,213],"is":[3,23,68,126,214],"an":[4,75],"essential":[5],"tool":[6],"across":[7,154],"numerous":[8],"domains,":[9],"yet":[10],"traditional":[11,165],"models":[12,153,166,205],"often":[13],"falter":[14],"when":[15],"faced":[16],"with":[17,149],"unilateral":[18,38,70],"boundary":[19,39],"conditions,":[20],"where":[21,209],"data":[22,111,121],"systematically":[24],"overestimated":[25],"or":[26],"underestimated.":[27],"This":[28,188],"paper":[29],"introduces":[30],"a":[31,53,101,116,133],"novel":[32],"approach":[33,67,179],"to":[34,56,128,164],"the":[35,46,69,88,98,120,137,141,175,191],"task":[36],"of":[37,65,90,100,119,136,143,177],"time":[40,211],"forecasting.":[42],"Our":[43,170],"research":[44,195],"bridges":[45],"gap":[47],"in":[48,84,162,196,206],"existing":[49,168],"methods":[50,145],"by":[51],"proposing":[52],"specialized":[54],"framework":[55],"accurately":[57,109],"forecast":[58],"within":[59],"these":[60],"skewed":[61],"datasets.":[62],"The":[63],"cornerstone":[64],"our":[66,144,178],"mean":[71],"square":[72],"error":[73],"(UMSE),":[74],"asymmetric":[76],"loss":[77],"function":[78],"that":[79,105],"strategically":[80],"addresses":[81],"underestimation":[82],"biases":[83],"training":[85],"data,":[86],"improving":[87],"precision":[89],"forecasts.":[91],"We":[92,139],"further":[93],"enhance":[94],"model":[95,103],"performance":[96],"through":[97,146],"implementation":[99],"dual":[102],"structure":[104],"processes":[106],"underestimated":[107],"and":[108,151,160,167,185],"estimated":[110],"points":[112],"separately,":[113],"allowing":[114],"for":[115,193,202],"nuanced":[117],"analysis":[118],"trends.":[122],"Additionally,":[123],"feature":[124],"reconstruction":[125],"employed":[127],"recapture":[129],"obscured":[130],"dynamics,":[131],"ensuring":[132],"comprehensive":[134],"understanding":[135],"data.":[138],"demonstrate":[140],"effectiveness":[142],"extensive":[147],"experimentation":[148],"LightGBM":[150],"GRU":[152],"diverse":[155],"datasets,":[156],"showcasing":[157],"superior":[158],"accuracy":[159],"robustness":[161],"comparison":[163],"methods.":[169],"findings":[171],"not":[172],"only":[173],"validate":[174],"efficacy":[176],"but":[180],"also":[181],"reveal":[182],"its":[183],"model-independence":[184],"broad":[186],"applicability.":[187],"work":[189],"lays":[190],"groundwork":[192],"future":[194],"this":[197],"domain,":[198],"opening":[199],"new":[200],"avenues":[201],"sophisticated":[203],"analytical":[204],"various":[207],"industries":[208],"precise":[210],"crucial.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}