{"id":"https://openalex.org/W2099343990","doi":"https://doi.org/10.1109/ijcnn.2004.1380205","title":"Double quantization forecasting method for filling missing data in the CATS time series","display_name":"Double quantization forecasting method for filling missing data in the CATS time series","publication_year":2005,"publication_date":"2005-04-05","ids":{"openalex":"https://openalex.org/W2099343990","doi":"https://doi.org/10.1109/ijcnn.2004.1380205","mag":"2099343990"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2004.1380205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1380205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-00141472v1/file/IJCNN_2004_lee_simon_Double_quantization_forecasting_method_for_filling.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026873073","display_name":"Gyula Simon","orcid":"https://orcid.org/0000-0003-0296-3399"},"institutions":[{"id":"https://openalex.org/I95674353","display_name":"UCLouvain","ror":"https://ror.org/02495e989","country_code":"BE","type":"education","lineage":["https://openalex.org/I95674353"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"G. Simon","raw_affiliation_strings":["Machine Learning Group, Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium","Machine Learning Group, Univ. Catholique de Louvain, Louvain-Ia-Neuve, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Learning Group, Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]},{"raw_affiliation_string":"Machine Learning Group, Univ. Catholique de Louvain, Louvain-Ia-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007892780","display_name":"John A. Lee","orcid":"https://orcid.org/0000-0001-5218-759X"},"institutions":[{"id":"https://openalex.org/I95674353","display_name":"UCLouvain","ror":"https://ror.org/02495e989","country_code":"BE","type":"education","lineage":["https://openalex.org/I95674353"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"J.A. Lee","raw_affiliation_strings":["Machine Learning Group, Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium","Machine Learning Group, Univ. Catholique de Louvain, Louvain-Ia-Neuve, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Learning Group, Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]},{"raw_affiliation_string":"Machine Learning Group, Univ. Catholique de Louvain, Louvain-Ia-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009959388","display_name":"Michel Verleysen","orcid":"https://orcid.org/0000-0003-4366-6155"},"institutions":[{"id":"https://openalex.org/I95674353","display_name":"UCLouvain","ror":"https://ror.org/02495e989","country_code":"BE","type":"education","lineage":["https://openalex.org/I95674353"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"M. Verleysen","raw_affiliation_strings":["Machine Learning Group, Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium","Machine Learning Group, Univ. Catholique de Louvain, Louvain-Ia-Neuve, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Machine Learning Group, Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]},{"raw_affiliation_string":"Machine Learning Group, Univ. Catholique de Louvain, Louvain-Ia-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110253771","display_name":"M. Patrick Cottrell","orcid":null},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210116548","display_name":"Laboratoire de Statistique Th\u00e9orique et Appliqu\u00e9e","ror":"https://ror.org/01vnn4t89","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210116548","https://openalex.org/I4210141950"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"M. Cottrell","raw_affiliation_strings":["SAMOS-MATISSE, UMR CNRS 8595, Universit\u00e9 Paris l Path\u00e9on Sorbonne, Paris, France","Statistique Appliqu\u00e9e et MOd\u00e9lisation Stochastique"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SAMOS-MATISSE, UMR CNRS 8595, Universit\u00e9 Paris l Path\u00e9on Sorbonne, Paris, France","institution_ids":["https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Statistique Appliqu\u00e9e et MOd\u00e9lisation Stochastique","institution_ids":["https://openalex.org/I4210116548"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9107,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.8144703,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"2","issue":null,"first_page":"1635","last_page":"1640"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9947999715805054,"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":0.9947999715805054,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9854999780654907,"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/vector-quantization","display_name":"Vector quantization","score":0.6906287670135498},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6021986603736877},{"id":"https://openalex.org/keywords/scalar","display_name":"Scalar (mathematics)","score":0.5535276532173157},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5453864336013794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5002105236053467},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4740026891231537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4363785684108734},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4172459840774536},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4156477451324463},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40547358989715576},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3421524167060852},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1785581409931183}],"concepts":[{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.6906287670135498},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6021986603736877},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.5535276532173157},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5453864336013794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5002105236053467},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4740026891231537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4363785684108734},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4172459840774536},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4156477451324463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40547358989715576},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3421524167060852},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1785581409931183},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn.2004.1380205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1380205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-00141472v1","is_oa":true,"landing_page_url":"https://hal.science/hal-00141472","pdf_url":"https://hal.science/hal-00141472v1/file/IJCNN_2004_lee_simon_Double_quantization_forecasting_method_for_filling.pdf","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks, Jul 2024, Budapest, Hungary. pp.1635-1640","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:dial.uclouvain.be:boreal:110971","is_oa":false,"landing_page_url":"http://hdl.handle.net/2078.1/110971","pdf_url":null,"source":{"id":"https://openalex.org/S4306401902","display_name":"Digital Access to Libraries (Universit\u00e9 catholique de Louvain (UCL), l'Universit\u00e9 de Namur (UNamur) and the Universit\u00e9 Saint-Louis (USL-B))","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I95674353","host_organization_name":"UCLouvain","host_organization_lineage":["https://openalex.org/I95674353"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-00141472v1","is_oa":true,"landing_page_url":"https://hal.science/hal-00141472","pdf_url":"https://hal.science/hal-00141472v1/file/IJCNN_2004_lee_simon_Double_quantization_forecasting_method_for_filling.pdf","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks, Jul 2024, Budapest, Hungary. pp.1635-1640","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2099343990.pdf","grobid_xml":"https://content.openalex.org/works/W2099343990.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W31148063","https://openalex.org/W1549386224","https://openalex.org/W1559504284","https://openalex.org/W1639729165","https://openalex.org/W2029401646","https://openalex.org/W2059135806","https://openalex.org/W2089844711","https://openalex.org/W2128685334","https://openalex.org/W2138822572","https://openalex.org/W2139581666","https://openalex.org/W2167815848","https://openalex.org/W3127780702","https://openalex.org/W4206504283","https://openalex.org/W4213332169","https://openalex.org/W6601254879","https://openalex.org/W6678993266","https://openalex.org/W6680456997","https://openalex.org/W6790056436"],"related_works":["https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2085630472","https://openalex.org/W1977098485","https://openalex.org/W4285201053","https://openalex.org/W3209251257"],"abstract_inverted_index":{"The":[0,69],"double":[1,74],"vector":[2,53,75],"quantization":[3,76],"forecasting":[4,89],"method":[5,31,77],"based":[6],"on":[7,85],"Kohonen":[8],"self-organizing":[9],"maps":[10],"is":[11,32,67],"applied":[12],"to":[13,35,61,81],"predict":[14,36],"the":[15,19,27,30,33,46,49,52,56,63,73],"missing":[16],"values":[17,41,84],"of":[18,26,29,39,51,58,72],"CATS":[20],"competition":[21],"data":[22],"set.":[23],"As":[24],"one":[25],"features":[28],"ability":[34],"vectors":[37],"instead":[38],"scalar":[40],"in":[42],"a":[43,86],"single":[44],"step,":[45],"compromise":[47],"between":[48],"size":[50],"prediction":[54,65],"and":[55],"number":[57],"repetitions":[59],"needed":[60],"reach":[62],"required":[64],"horizon":[66],"studied.":[68],"long-term":[70,88],"stability":[71],"makes":[78],"it":[79],"possible":[80],"obtain":[82],"reliable":[83],"rather":[87],"horizon.":[90]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}