{"id":"https://openalex.org/W2094153195","doi":"https://doi.org/10.1109/ijcnn.2014.6889666","title":"A Monte Carlo strategy for structured multiple-step-ahead time series prediction","display_name":"A Monte Carlo strategy for structured multiple-step-ahead time series prediction","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2094153195","doi":"https://doi.org/10.1109/ijcnn.2014.6889666","mag":"2094153195"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2014.6889666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","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/A5072869049","display_name":"Gianluca Bontempi","orcid":"https://orcid.org/0000-0001-8621-316X"},"institutions":[{"id":"https://openalex.org/I132053463","display_name":"Universit\u00e9 Libre de Bruxelles","ror":"https://ror.org/01r9htc13","country_code":"BE","type":"education","lineage":["https://openalex.org/I132053463"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Gianluca Bontempi","raw_affiliation_strings":["Universite Libre de Bruxelles, Bruxelles, Bruxelles, BE","Machine Learning Group, Univ. Libre de Bruxelles, Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Universite Libre de Bruxelles, Bruxelles, Bruxelles, BE","institution_ids":["https://openalex.org/I132053463"]},{"raw_affiliation_string":"Machine Learning Group, Univ. Libre de Bruxelles, Brussels, Belgium","institution_ids":["https://openalex.org/I132053463"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5072869049"],"corresponding_institution_ids":["https://openalex.org/I132053463"],"apc_list":null,"apc_paid":null,"fwci":0.4058,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70218791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"135","issue":null,"first_page":"853","last_page":"858"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9976999759674072,"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":0.9976999759674072,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9861999750137329,"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7287957668304443},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6814599633216858},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6013409495353699},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5787534713745117},{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.5741109848022461},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5675995945930481},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5445965528488159},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5013577938079834},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4009948968887329},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3996903598308563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.349903404712677},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.341804563999176},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15676069259643555},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07460790872573853}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7287957668304443},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6814599633216858},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6013409495353699},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5787534713745117},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.5741109848022461},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5675995945930481},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5445965528488159},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5013577938079834},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4009948968887329},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3996903598308563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.349903404712677},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.341804563999176},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15676069259643555},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07460790872573853},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/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/ijcnn.2014.6889666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889666","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321584","display_name":"F\u00e9d\u00e9ration Wallonie-Bruxelles","ror":"https://ror.org/04q01pf08"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1483307070","https://openalex.org/W1515020792","https://openalex.org/W1558248317","https://openalex.org/W1897785919","https://openalex.org/W1907195750","https://openalex.org/W1985093013","https://openalex.org/W2003706483","https://openalex.org/W2014928429","https://openalex.org/W2028072219","https://openalex.org/W2058398751","https://openalex.org/W2147739825","https://openalex.org/W2153787847","https://openalex.org/W2170681242","https://openalex.org/W2481648081","https://openalex.org/W2803316390","https://openalex.org/W2811189031","https://openalex.org/W2913340405","https://openalex.org/W3123760665","https://openalex.org/W4292403327","https://openalex.org/W6616610000","https://openalex.org/W6639581358","https://openalex.org/W6654117996"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W4230315250"],"abstract_inverted_index":{"Forecasting":[0],"a":[1,6,38,52,93,107,118,136,157],"time":[2],"series":[3,53],"multiple-step-ahead":[4],"is":[5,59,130,164],"challenging":[7],"problem":[8,50,102,108],"for":[9],"several":[10],"reasons:":[11],"the":[12,16,19,22,35,49,61,64,67,77,83,101,128,140,153,169],"accumulation":[13],"of":[14,21,37,41,54,63,82,103,109,127,139,149],"errors,":[15],"noise,":[17],"and":[18,26,66,75,79,143,156,166],"complexity":[20],"dependency":[23],"between":[24],"past":[25],"far":[27],"future":[28],"which":[29,113],"has":[30],"to":[31,45,51,85,91],"be":[32,86,115],"inferred":[33],"on":[34],"basis":[36],"limited":[39],"amount":[40],"data.":[42],"Traditional":[43],"approaches":[44,73],"multi-step-ahead":[46],"forecasting":[47,105],"reduce":[48],"single-output":[55],"prediction":[56],"tasks.":[57],"This":[58,88],"notably":[60],"case":[62],"Iterated":[65,142],"Direct":[68,144],"approaches.":[69,145],"More":[70],"recently,":[71],"multiple-output":[72],"appeared":[74],"stressed":[76],"multivariate":[78,111],"structured":[80],"nature":[81],"output":[84],"predicted.":[87],"paper":[89],"intends":[90],"go":[92],"step":[94],"further":[95],"in":[96],"this":[97,132,162],"direction":[98],"by":[99,117],"formulating":[100],"multi-step-ahed":[104],"as":[106],"conditional":[110],"estimation":[112],"can":[114],"addressed":[116],"Monte":[119],"Carlo":[120],"importance":[121],"sampling":[122],"strategy.":[123],"The":[124,146],"interesting":[125],"aspect":[126],"approach":[129,163],"that":[131,161],"probabilistic":[133],"formulation":[134],"allows":[135],"natural":[137],"integration":[138],"traditional":[141],"extensive":[147],"assessment":[148],"our":[150],"algorithm":[151],"with":[152,168],"NN5,":[154],"NN3":[155],"synthetic":[158],"benchmark":[159],"shows":[160],"promising":[165],"competitive":[167],"state-of-the-art.":[170]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
