{"id":"https://openalex.org/W1531794620","doi":"https://doi.org/10.1109/ijcnn.2003.1223705","title":"Multivariate time series model discovery with similarity-based neuro-fuzzy networks and genetic algorithms","display_name":"Multivariate time series model discovery with similarity-based neuro-fuzzy networks and genetic algorithms","publication_year":2004,"publication_date":"2004-03-22","ids":{"openalex":"https://openalex.org/W1531794620","doi":"https://doi.org/10.1109/ijcnn.2003.1223705","mag":"1531794620"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2003.1223705","is_oa":false,"landing_page_url":"http://doi.org/10.1109/ijcnn.2003.1223705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://nrc-publications.canada.ca/eng/view/accepted/?id=2f914f35-4cf4-4265-9eea-f194b906e1bb","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019572093","display_name":"Julio J. Vald\u00e9s","orcid":"https://orcid.org/0000-0003-2930-0325"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"J.J. Valdes","raw_affiliation_strings":["Inst. for Inf. Technol., Nat. Res. Council of Canada, Ottawa, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Inst. for Inf. Technol., Nat. Res. Council of Canada, Ottawa, ON, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111427734","display_name":"Alan J. Barton","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A.J. Barton","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019572093"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8485,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.86976219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"1945","last_page":"1950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9977999925613403,"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":0.9977999925613403,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9955000281333923,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9781000018119812,"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":0.6519399881362915},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6280808448791504},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5981751084327698},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5424720644950867},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5393054485321045},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5140377283096313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5093306303024292},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4544419050216675},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4452986717224121},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.41778823733329773},{"id":"https://openalex.org/keywords/neuro-fuzzy","display_name":"Neuro-fuzzy","score":0.4176274836063385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41451993584632874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3800857365131378},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.2728075087070465}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6519399881362915},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6280808448791504},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5981751084327698},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5424720644950867},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5393054485321045},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5140377283096313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5093306303024292},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4544419050216675},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4452986717224121},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.41778823733329773},{"id":"https://openalex.org/C29470771","wikidata":"https://www.wikidata.org/wiki/Q4165150","display_name":"Neuro-fuzzy","level":4,"score":0.4176274836063385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41451993584632874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3800857365131378},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.2728075087070465},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2003.1223705","is_oa":false,"landing_page_url":"http://doi.org/10.1109/ijcnn.2003.1223705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","raw_type":"proceedings-article"},{"id":"pmh:oai:cisti-icist.nrc-cnrc.ca:cistinparc:8913996","is_oa":true,"landing_page_url":"https://nrc-publications.canada.ca/fra/voir/objet/?id=2f914f35-4cf4-4265-9eea-f194b906e1bb","pdf_url":"https://nrc-publications.canada.ca/eng/view/accepted/?id=2f914f35-4cf4-4265-9eea-f194b906e1bb","source":{"id":"https://openalex.org/S7407055245","display_name":"NPARC","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:cisti-icist.nrc-cnrc.ca:cistinparc:8913996","is_oa":true,"landing_page_url":"https://nrc-publications.canada.ca/fra/voir/objet/?id=2f914f35-4cf4-4265-9eea-f194b906e1bb","pdf_url":"https://nrc-publications.canada.ca/eng/view/accepted/?id=2f914f35-4cf4-4265-9eea-f194b906e1bb","source":{"id":"https://openalex.org/S7407055245","display_name":"NPARC","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322676","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1531794620.pdf","grobid_xml":"https://content.openalex.org/works/W1531794620.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W1605328303","https://openalex.org/W1898437568","https://openalex.org/W1983175601","https://openalex.org/W2105921217"],"related_works":["https://openalex.org/W2406638334","https://openalex.org/W2472172556","https://openalex.org/W2324780611","https://openalex.org/W1990068454","https://openalex.org/W2280920478","https://openalex.org/W1991765889","https://openalex.org/W1570805059","https://openalex.org/W2357266745","https://openalex.org/W1578824628","https://openalex.org/W3122321533"],"abstract_inverted_index":{"This":[0,26],"paper":[1],"studies":[2],"the":[3,76,81,89],"properties":[4],"of":[5,34,41,55,83,106],"a":[6,35,48,53,69],"hybrid":[7,19],"technique":[8],"for":[9,74],"model":[10,77],"discovery":[11,78],"in":[12],"multivariate":[13,71],"time":[14,72],"series,":[15,44],"using":[16],"similarity":[17],"based":[18],"neuro-fuzzy":[20],"neural":[21],"networks":[22],"and":[23,45,57,62,80,100],"genetic":[24],"algorithms.":[25],"method":[27,90],"discovers":[28,94],"<em>dependency":[29],"patterns</em>":[30],"relating":[31],"future":[32],"values":[33,40],"target":[36],"series":[37,73],"with":[38,68],"past":[39],"all":[42],"examined":[43],"also":[46],"constructs":[47],"prediction":[49],"function.":[50],"It":[51],"accepts":[52],"mixture":[54],"numeric":[56],"non-numeric":[58],"variables,":[59],"fuzzy":[60],"information,":[61],"missing":[63,84,107],"values.":[64,85],"Experiments":[65],"were":[66],"made":[67],"real":[70],"studying":[75],"ability":[79],"influence":[82],"Results":[86],"show":[87],"that":[88],"is":[91,101],"very":[92],"robust,":[93],"relevant":[95],"interdependencies,":[96],"gives":[97],"accurate":[98],"predictions":[99],"tolerant":[102],"to":[103],"considerable":[104],"proportions":[105],"information.":[108]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}