{"id":"https://openalex.org/W2546646706","doi":"https://doi.org/10.1109/cist.2014.7016596","title":"A comparative study of predictive algorithms for time series forecasting","display_name":"A comparative study of predictive algorithms for time series forecasting","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2546646706","doi":"https://doi.org/10.1109/cist.2014.7016596","mag":"2546646706"},"language":"en","primary_location":{"id":"doi:10.1109/cist.2014.7016596","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cist.2014.7016596","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 Third IEEE International Colloquium in Information Science and Technology (CIST)","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/A5028774895","display_name":"Meryem Ouahilal","orcid":"https://orcid.org/0000-0001-6239-7355"},"institutions":[{"id":"https://openalex.org/I4210157007","display_name":"\u00c9cole Normale Sup\u00e9rieure de T\u00e9touan","ror":"https://ror.org/04pry7b16","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210157007"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Ouahilal Meryem","raw_affiliation_strings":["Faculty of science, Tetuan, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of science, Tetuan, Morocco","institution_ids":["https://openalex.org/I4210157007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063354884","display_name":"Ismail Jellouli","orcid":"https://orcid.org/0009-0004-4153-2406"},"institutions":[{"id":"https://openalex.org/I4210157007","display_name":"\u00c9cole Normale Sup\u00e9rieure de T\u00e9touan","ror":"https://ror.org/04pry7b16","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210157007"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Jellouli Ismail","raw_affiliation_strings":["Faculty of science, Tetuan, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of science, Tetuan, Morocco","institution_ids":["https://openalex.org/I4210157007"]}]},{"author_position":"last","author":{"id":null,"display_name":"El Mohajir Mohammed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"El Mohajir Mohammed","raw_affiliation_strings":["Faculty of science, USMBA Fez, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of science, USMBA Fez, Morocco","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2605,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84411272,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"68","last_page":"73"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9997000098228455,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9997000098228455,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9958000183105469,"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":0.9955000281333923,"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":0.6937190294265747},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6644203662872314},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6198268532752991},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6172208786010742},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.607796847820282},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5348109006881714},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.49729278683662415},{"id":"https://openalex.org/keywords/predictive-analytics","display_name":"Predictive analytics","score":0.4928324222564697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48613306879997253},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47815045714378357},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4584992825984955},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3959285616874695},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3429015278816223},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1610938012599945},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11759275197982788}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6937190294265747},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6644203662872314},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6198268532752991},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6172208786010742},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.607796847820282},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5348109006881714},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.49729278683662415},{"id":"https://openalex.org/C83209312","wikidata":"https://www.wikidata.org/wiki/Q1053367","display_name":"Predictive analytics","level":2,"score":0.4928324222564697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48613306879997253},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47815045714378357},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4584992825984955},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3959285616874695},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3429015278816223},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1610938012599945},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11759275197982788},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cist.2014.7016596","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cist.2014.7016596","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 Third IEEE International Colloquium in Information Science and Technology (CIST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1981551863","https://openalex.org/W2015374985","https://openalex.org/W2105119576","https://openalex.org/W2117014758","https://openalex.org/W2172073485","https://openalex.org/W2182617889","https://openalex.org/W2322661943","https://openalex.org/W2334160455","https://openalex.org/W2477834368","https://openalex.org/W4210616753","https://openalex.org/W6686054988","https://openalex.org/W6703061134"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2136232598"],"abstract_inverted_index":{"Forecasting":[0],"is":[1],"an":[2],"important":[3],"activity":[4],"in":[5,72,78],"economics,":[6],"finance,":[7],"marketing":[8],"and":[9,15,34,69],"various":[10],"other":[11,113],"domains":[12],"like":[13],"environmental":[14],"social":[16],"sciences.":[17],"There":[18],"are":[19,46],"several":[20],"methods":[21,33],"for":[22,49,84],"making":[23],"forecasts,":[24],"but":[25],"they":[26],"all":[27],"fall":[28],"into":[29],"two":[30,114],"categories:":[31],"causal":[32],"time":[35,44],"series":[36,45,83],"methods.":[37],"In":[38,51],"many":[39],"cases,":[40],"predictive":[41,85],"algorithms":[42,115],"implementing":[43,81],"good":[47,118],"candidates":[48],"forecasting.":[50],"this":[52],"paper":[53],"we":[54,94],"run":[55],"a":[56,117],"comparative":[57],"study":[58],"of":[59,61,80,91],"three":[60],"these":[62,92],"algorithms:":[63],"Linear":[64],"Regression,":[65],"Support":[66],"Vector":[67],"Machines":[68],"Multilayer":[70],"Perceptron":[71],"order":[73],"to":[74],"determine":[75],"their":[76],"performances":[77],"term":[79],"times":[82],"systems.":[86],"To":[87],"assess":[88],"the":[89,109],"performance":[90],"algorithms,":[93],"have":[95],"conducted":[96],"experiments":[97],"over":[98],"four":[99],"representative":[100],"datasets.":[101],"The":[102,112],"results":[103],"exhibit":[104],"that":[105],"linear":[106],"regression":[107],"produced":[108],"best":[110],"forecasts.":[111],"show":[116],"behavior":[119],"as":[120],"well.":[121]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
