{"id":"https://openalex.org/W2959892146","doi":"https://doi.org/10.1145/3309772.3309773","title":"Hybrid machine learning methods for demand forecasting","display_name":"Hybrid machine learning methods for demand forecasting","publication_year":2019,"publication_date":"2019-01-07","ids":{"openalex":"https://openalex.org/W2959892146","doi":"https://doi.org/10.1145/3309772.3309773","mag":"2959892146"},"language":"en","primary_location":{"id":"doi:10.1145/3309772.3309773","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3309772.3309773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Applications of Intelligent 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/A5054047561","display_name":"V\u00edctor \u00c1lvarez-L\u00f3pez","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112307","display_name":"Fundaci\u00f3n Centro Tecnol\u00f3gico de la Informaci\u00f3n y la Comunicaci\u00f3n","ror":"https://ror.org/01whh8488","country_code":"ES","type":"nonprofit","lineage":["https://openalex.org/I4210112307"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"V\u00edctor \u00c1lvarez-L\u00f3pez","raw_affiliation_strings":["CTIC Centro Tecnol\u00f3gico, Gij\u00f3n, Asturias, Spain"],"affiliations":[{"raw_affiliation_string":"CTIC Centro Tecnol\u00f3gico, Gij\u00f3n, Asturias, Spain","institution_ids":["https://openalex.org/I4210112307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084342487","display_name":"B. Rosario Campomanes-\u00c1lvarez","orcid":"https://orcid.org/0000-0002-4564-9263"},"institutions":[{"id":"https://openalex.org/I4210112307","display_name":"Fundaci\u00f3n Centro Tecnol\u00f3gico de la Informaci\u00f3n y la Comunicaci\u00f3n","ror":"https://ror.org/01whh8488","country_code":"ES","type":"nonprofit","lineage":["https://openalex.org/I4210112307"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"B. Rosario Campomanes-\u00c1lvarez","raw_affiliation_strings":["CTIC Centro Tecnol\u00f3gico, Gij\u00f3n, Asturias, Spain"],"affiliations":[{"raw_affiliation_string":"CTIC Centro Tecnol\u00f3gico, Gij\u00f3n, Asturias, Spain","institution_ids":["https://openalex.org/I4210112307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029070486","display_name":"Pelayo Quir\u00f3s","orcid":"https://orcid.org/0000-0002-0500-9034"},"institutions":[{"id":"https://openalex.org/I4210112307","display_name":"Fundaci\u00f3n Centro Tecnol\u00f3gico de la Informaci\u00f3n y la Comunicaci\u00f3n","ror":"https://ror.org/01whh8488","country_code":"ES","type":"nonprofit","lineage":["https://openalex.org/I4210112307"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Pelayo Quir\u00f3s","raw_affiliation_strings":["CTIC Centro Tecnol\u00f3gico, Gij\u00f3n, Asturias, Spain"],"affiliations":[{"raw_affiliation_string":"CTIC Centro Tecnol\u00f3gico, Gij\u00f3n, Asturias, Spain","institution_ids":["https://openalex.org/I4210112307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054047561"],"corresponding_institution_ids":["https://openalex.org/I4210112307"],"apc_list":null,"apc_paid":null,"fwci":0.1659,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.43292009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9970999956130981,"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":0.9970999956130981,"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":0.9930999875068665,"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":0.9904999732971191,"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":0.7091530561447144},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6678389310836792},{"id":"https://openalex.org/keywords/demand-forecasting","display_name":"Demand forecasting","score":0.6529762744903564},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5674539804458618},{"id":"https://openalex.org/keywords/instant","display_name":"Instant","score":0.5595690608024597},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5397186875343323},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.49154314398765564},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4486987292766571},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.44228455424308777},{"id":"https://openalex.org/keywords/simple-linear-regression","display_name":"Simple linear regression","score":0.4412629008293152},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4322251081466675},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38298824429512024},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17394021153450012},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15695339441299438},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.1511772871017456}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7091530561447144},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6678389310836792},{"id":"https://openalex.org/C193809577","wikidata":"https://www.wikidata.org/wiki/Q3409300","display_name":"Demand forecasting","level":2,"score":0.6529762744903564},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5674539804458618},{"id":"https://openalex.org/C2779432360","wikidata":"https://www.wikidata.org/wiki/Q16963779","display_name":"Instant","level":2,"score":0.5595690608024597},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5397186875343323},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.49154314398765564},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4486987292766571},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.44228455424308777},{"id":"https://openalex.org/C149769383","wikidata":"https://www.wikidata.org/wiki/Q7520804","display_name":"Simple linear regression","level":3,"score":0.4412629008293152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4322251081466675},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38298824429512024},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17394021153450012},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15695339441299438},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.1511772871017456},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3309772.3309773","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3309772.3309773","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Applications of Intelligent Systems","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":15,"referenced_works":["https://openalex.org/W1663973292","https://openalex.org/W1678356000","https://openalex.org/W1761010383","https://openalex.org/W1780185704","https://openalex.org/W1975075722","https://openalex.org/W2025053102","https://openalex.org/W2075661246","https://openalex.org/W2113242816","https://openalex.org/W2119821739","https://openalex.org/W2132782512","https://openalex.org/W2573526403","https://openalex.org/W2769957979","https://openalex.org/W2800705832","https://openalex.org/W4301861531","https://openalex.org/W6738178268"],"related_works":["https://openalex.org/W2356370096","https://openalex.org/W2794694000","https://openalex.org/W2094154142","https://openalex.org/W2350999733","https://openalex.org/W2392387319","https://openalex.org/W2359725054","https://openalex.org/W4287262429","https://openalex.org/W4287262247","https://openalex.org/W4287613691","https://openalex.org/W1999916546"],"abstract_inverted_index":{"This":[0,78],"paper":[1],"is":[2,39,48,68,80],"focused":[3],"on":[4],"demand":[5,87],"forecasting,":[6],"where":[7,44],"the":[8,24,54,72,91],"orders":[9],"from":[10],"each":[11,27],"customer":[12],"are":[13,32],"generated":[14,69],"periodically":[15],"but":[16],"in":[17,50,57],"a":[18,66],"non-continuous":[19],"way,":[20],"so":[21],"most":[22],"of":[23,36,75],"values":[25],"for":[26,89,94],"client":[28],"and":[29,64],"temporal":[30,55],"instant":[31],"zeros.":[33],"The":[34],"application":[35,84],"regression":[37,67,103],"models":[38],"compared":[40],"to":[41,52,70,85,101],"hybrid":[42],"methods,":[43],"an":[45,59,83],"initial":[46],"classification":[47],"considered":[49],"order":[51,60],"identify":[53],"instants":[56],"which":[58],"has":[61],"been":[62],"predicted,":[63],"afterwards,":[65],"obtain":[71],"predicted":[73],"amount":[74],"such":[76],"order.":[77],"procedure":[79],"complemented":[81],"by":[82],"real":[86],"data,":[88],"selecting":[90],"proper":[92],"methods":[93],"both":[95],"phases,":[96],"as":[97,99],"well":[98],"comparing":[100],"simple":[102],"models.":[104]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}