{"id":"https://openalex.org/W4410536524","doi":"https://doi.org/10.1109/tai.2025.3571377","title":"SRLinear: Lightweight Long-Term Time Series Forecasting via Symbolic Regression","display_name":"SRLinear: Lightweight Long-Term Time Series Forecasting via Symbolic Regression","publication_year":2025,"publication_date":"2025-05-20","ids":{"openalex":"https://openalex.org/W4410536524","doi":"https://doi.org/10.1109/tai.2025.3571377"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2025.3571377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2025.3571377","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hongbo Zhao","orcid":"https://orcid.org/0009-0007-9680-2268"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongbo Zhao","raw_affiliation_strings":["Laboratory of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","Lab of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0007-9680-2268","affiliations":[{"raw_affiliation_string":"Laboratory of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Lab of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041504960","display_name":"Hengzhe Zhang","orcid":"https://orcid.org/0000-0002-2254-8304"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Hengzhe Zhang","raw_affiliation_strings":["Centre for Data Science and Artificial Intelligence and the School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":"https://orcid.org/0000-0002-2254-8304","affiliations":[{"raw_affiliation_string":"Centre for Data Science and Artificial Intelligence and the School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chutian Tian","orcid":"https://orcid.org/0009-0006-4095-3983"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chutian Tian","raw_affiliation_strings":["Laboratory of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","Lab of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0006-4095-3983","affiliations":[{"raw_affiliation_string":"Laboratory of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Lab of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001916237","display_name":"Zhi Wei","orcid":"https://orcid.org/0000-0001-6059-4267"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhi Wei","raw_affiliation_strings":["Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA","Department of Computer Science, New Jersey Institute of Technology, Newark,, NJ, USA"],"raw_orcid":"https://orcid.org/0000-0001-6059-4267","affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]},{"raw_affiliation_string":"Department of Computer Science, New Jersey Institute of Technology, Newark,, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050248676","display_name":"Aimin Zhou","orcid":"https://orcid.org/0000-0002-4768-5946"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aimin Zhou","raw_affiliation_strings":["Laboratory of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","Lab of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4768-5946","affiliations":[{"raw_affiliation_string":"Laboratory of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]},{"raw_affiliation_string":"Lab of Artificial Intelligence for Education and the School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04851895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":"1","first_page":"210","last_page":"224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9632999897003174,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9632999897003174,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9312999844551086,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.733285129070282},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.622697114944458},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5812304019927979},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5483345985412598},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.526089072227478},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4527015686035156},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4074218273162842},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4061213731765747},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35164976119995117},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3371331989765167},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2504366636276245},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06664642691612244}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.733285129070282},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.622697114944458},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5812304019927979},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5483345985412598},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.526089072227478},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4527015686035156},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4074218273162842},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4061213731765747},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35164976119995117},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3371331989765167},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2504366636276245},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06664642691612244},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2025.3571377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2025.3571377","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2126831543","https://openalex.org/W2227929282","https://openalex.org/W2295598076","https://openalex.org/W2750973274","https://openalex.org/W2892035503","https://openalex.org/W2963608065","https://openalex.org/W2971724044","https://openalex.org/W2980994438","https://openalex.org/W3007075806","https://openalex.org/W3019433526","https://openalex.org/W3177318507","https://openalex.org/W4205678345","https://openalex.org/W4312702461","https://openalex.org/W4321448314","https://openalex.org/W4362655576","https://openalex.org/W4381245607","https://openalex.org/W4381326995","https://openalex.org/W4382203079","https://openalex.org/W4382239237","https://openalex.org/W4384024837","https://openalex.org/W4393147199","https://openalex.org/W4393157509","https://openalex.org/W4393159606","https://openalex.org/W4393159654","https://openalex.org/W4393159664","https://openalex.org/W4393159718","https://openalex.org/W4393177791","https://openalex.org/W4399695543","https://openalex.org/W4400373628","https://openalex.org/W4400909761","https://openalex.org/W4401353384"],"related_works":["https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W1970763357"],"abstract_inverted_index":{"Long-term":[0],"Time":[1],"Series":[2],"Forecasting":[3],"(LTSF)":[4],"plays":[5],"a":[6,60,92,141],"crucial":[7],"role":[8],"in":[9,20,66],"various":[10],"fields,":[11],"including":[12],"energy":[13],"consumption":[14],"and":[15,44,94,112,128,138,168],"weather":[16],"prediction.":[17],"Recent":[18],"advancements":[19],"deep":[21],"learning,":[22],"particularly":[23],"transformer":[24],"models,":[25],"have":[26,57],"significantly":[27],"improved":[28],"LTSF":[29,67,96],"performance.":[30],"However,":[31],"these":[32,74,87,117,132],"models":[33,56,75],"often":[34],"face":[35],"criticism":[36],"for":[37,145],"their":[38,51,83],"lack":[39],"of":[40,201],"transparency,":[41],"limited":[42],"interpretability,":[43],"high":[45],"computational":[46,152],"requirements,":[47],"which":[48,134],"can":[49,193],"hinder":[50],"practical":[52],"application.":[53],"Simple":[54],"linear":[55,143],"emerged":[58],"as":[59,73],"promising":[61],"alternative,":[62],"demonstrating":[63],"excellent":[64],"performance":[65],"while":[68,154],"offering":[69],"greater":[70],"simplicity.":[71],"Yet,":[72],"become":[76],"more":[77],"complex,":[78],"they":[79],"tend":[80],"to":[81,125],"lose":[82],"advantages.":[84],"To":[85],"address":[86],"challenges,":[88],"we":[89],"introduce":[90],"SRLinear,":[91],"lightweight":[93,149],"interpretable":[95,129,190],"framework":[97,187],"based":[98],"on":[99,175,182],"symbolic":[100,123,155,158],"regression.":[101],"Our":[102,205],"approach":[103],"first":[104],"breaks":[105],"down":[106],"time":[107],"series":[108],"data":[109],"into":[110,118,163],"seasonal":[111],"trend":[113],"components,":[114,133],"then":[115,136],"divides":[116],"smaller":[119],"segments.":[120],"We":[121,172],"use":[122],"regression":[124,156],"extract":[126],"meaningful":[127],"features":[130,191],"from":[131],"are":[135],"combined":[137],"processed":[139],"through":[140],"single":[142],"layer":[144],"future":[146],"predictions.":[147],"This":[148],"design":[150],"ensures":[151],"efficiency,":[153],"generates":[157],"expressions,":[159],"providing":[160],"clear":[161],"insights":[162],"the":[164,198,202],"feature":[165],"extraction":[166],"process":[167],"enhancing":[169,197],"model":[170],"interpretability.":[171],"tested":[173],"SRLinear":[174],"8":[176],"real-world":[177],"datasets,":[178],"achieving":[179],"state-of-the-art":[180],"results":[181],"multiple":[183],"benchmarks.":[184],"Importantly,":[185],"our":[186],"produces":[188],"highly":[189],"that":[192],"be":[194],"easily":[195],"visualized,":[196],"overall":[199],"transparency":[200],"prediction":[203],"process.":[204],"code":[206],"is":[207],"publicly":[208],"available":[209],"at":[210],"https://github.com/fantasy-99/SRLinear.":[211]},"counts_by_year":[],"updated_date":"2026-01-08T20:05:33.558190","created_date":"2025-10-10T00:00:00"}