{"id":"https://openalex.org/W2097338558","doi":"https://doi.org/10.1109/fuzzy.2010.5584001","title":"Meta-learning for time series forecasting in the NN GC1 competition","display_name":"Meta-learning for time series forecasting in the NN GC1 competition","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2097338558","doi":"https://doi.org/10.1109/fuzzy.2010.5584001","mag":"2097338558"},"language":"en","primary_location":{"id":"doi:10.1109/fuzzy.2010.5584001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2010.5584001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Fuzzy Systems","raw_type":"proceedings-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":"https://openalex.org/A5083524022","display_name":"Christiane Lemke","orcid":"https://orcid.org/0000-0001-5259-2181"},"institutions":[{"id":"https://openalex.org/I9300472","display_name":"Bournemouth University","ror":"https://ror.org/05wwcw481","country_code":"GB","type":"education","lineage":["https://openalex.org/I9300472"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Christiane Lemke","raw_affiliation_strings":["Smart Technology Research Centre, School of Design, Engineering and Computing, Bournemouth University, Poole, UK","Smart Technology Research Centre, School of Design, Engineering and Computing, Bournemouth University, Poole House, Talbot Campus, Fern Barrow, Poole, BH12 5BB"],"affiliations":[{"raw_affiliation_string":"Smart Technology Research Centre, School of Design, Engineering and Computing, Bournemouth University, Poole, UK","institution_ids":["https://openalex.org/I9300472"]},{"raw_affiliation_string":"Smart Technology Research Centre, School of Design, Engineering and Computing, Bournemouth University, Poole House, Talbot Campus, Fern Barrow, Poole, BH12 5BB","institution_ids":["https://openalex.org/I9300472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083181106","display_name":"Bogdan Gabry\u015b","orcid":"https://orcid.org/0000-0002-0790-2846"},"institutions":[{"id":"https://openalex.org/I9300472","display_name":"Bournemouth University","ror":"https://ror.org/05wwcw481","country_code":"GB","type":"education","lineage":["https://openalex.org/I9300472"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bogdan Gabrys","raw_affiliation_strings":["Smart Technology Research Centre, School of Design, Engineering and Computing, Bournemouth University, Poole, UK","Smart Technology Research Centre, School of Design, Engineering and Computing, Bournemouth University, Poole House, Talbot Campus, Fern Barrow, Poole, BH12 5BB"],"affiliations":[{"raw_affiliation_string":"Smart Technology Research Centre, School of Design, Engineering and Computing, Bournemouth University, Poole, UK","institution_ids":["https://openalex.org/I9300472"]},{"raw_affiliation_string":"Smart Technology Research Centre, School of Design, Engineering and Computing, Bournemouth University, Poole House, Talbot Campus, Fern Barrow, Poole, BH12 5BB","institution_ids":["https://openalex.org/I9300472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083524022"],"corresponding_institution_ids":["https://openalex.org/I9300472"],"apc_list":null,"apc_paid":null,"fwci":2.3463,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.8914636,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","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"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9613999724388123,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9496999979019165,"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/computer-science","display_name":"Computer science","score":0.7348142266273499},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6835631132125854},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6280238628387451},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.623583972454071},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.591309130191803},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5854983329772949},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5751261711120605},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5396305322647095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5242921710014343},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.4789581596851349},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.45344218611717224},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.45225194096565247},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4482010304927826},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.15126627683639526},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13276883959770203},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08345699310302734}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7348142266273499},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6835631132125854},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6280238628387451},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.623583972454071},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.591309130191803},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5854983329772949},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5751261711120605},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5396305322647095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5242921710014343},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.4789581596851349},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.45344218611717224},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.45225194096565247},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4482010304927826},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.15126627683639526},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13276883959770203},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08345699310302734},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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":1,"locations":[{"id":"doi:10.1109/fuzzy.2010.5584001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2010.5584001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Fuzzy Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W27682692","https://openalex.org/W1503022246","https://openalex.org/W1528411633","https://openalex.org/W1535026045","https://openalex.org/W1582502377","https://openalex.org/W1586335931","https://openalex.org/W1598816125","https://openalex.org/W1600957637","https://openalex.org/W1605276600","https://openalex.org/W1975172114","https://openalex.org/W1977698057","https://openalex.org/W1985453523","https://openalex.org/W1989989024","https://openalex.org/W2007260464","https://openalex.org/W2022721685","https://openalex.org/W2025181367","https://openalex.org/W2038181716","https://openalex.org/W2045199291","https://openalex.org/W2048665112","https://openalex.org/W2057182962","https://openalex.org/W2079560958","https://openalex.org/W2091860924","https://openalex.org/W2093230975","https://openalex.org/W2095219562","https://openalex.org/W2137835385","https://openalex.org/W2145680191","https://openalex.org/W2167467747","https://openalex.org/W2171185425","https://openalex.org/W2980414587","https://openalex.org/W3122346463","https://openalex.org/W3123547113","https://openalex.org/W4239851718","https://openalex.org/W4285719527","https://openalex.org/W6634935632","https://openalex.org/W6769292430"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W4206952807"],"abstract_inverted_index":{"There":[0],"are":[1,137],"no":[2],"algorithms":[3],"that":[4],"generally":[5],"perform":[6],"better":[7,59],"or":[8,83],"worse":[9],"than":[10,60],"random":[11],"when":[12],"looking":[13],"at":[14],"all":[15],"possible":[16],"data":[17,73,118],"sets":[18],"according":[19],"to":[20,42,75,88,110],"the":[21,72,76,81,104,120],"no-free-lunch":[22],"theorem.":[23],"A":[24,129],"specific":[25,52,90],"forecasting":[26,102,133],"method":[27],"will":[28,48],"hence":[29],"naturally":[30],"have":[31,126],"different":[32,35],"performances":[33,77],"in":[34,62,103],"empirical":[36],"studies.":[37],"This":[38,92],"makes":[39],"it":[40],"impossible":[41],"draw":[43],"general":[44],"conclusions,":[45],"however,":[46],"there":[47],"of":[49,71,78,85,119,131],"course":[50],"be":[51],"problems":[53],"for":[54,99],"which":[55],"one":[56],"algorithm":[57,142],"performs":[58],"another":[61],"practice.":[63],"Meta-learning":[64],"exploits":[65],"this":[66],"fact":[67],"by":[68,147],"linking":[69],"characteristics":[70],"set":[74],"methods,":[79],"adapting":[80],"selection":[82],"combination":[84,135],"base":[86],"methods":[87],"a":[89,140],"problem.":[91],"contribution":[93],"describes":[94],"an":[95],"approach":[96],"using":[97,139],"meta-learning":[98],"time":[100],"series":[101],"NN":[105],"GC1":[106],"competition.":[107],"In":[108],"order":[109],"generate":[111],"bigger":[112],"and":[113,123,134],"more":[114],"reliable":[115],"meta-data":[116],"set,":[117],"past":[121,148],"NN3":[122],"NN5":[124],"competitions":[125],"been":[127],"included.":[128],"pool":[130],"individual":[132],"models":[136],"combined":[138],"ranking":[141],"with":[143],"weights":[144],"being":[145],"determined":[146],"performance":[149],"on":[150],"similar":[151],"series.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}