{"id":"https://openalex.org/W2138064036","doi":"https://doi.org/10.1109/fuzzy.2006.1681994","title":"HMM based Fuzzy Model for Time Series Prediction","display_name":"HMM based Fuzzy Model for Time Series Prediction","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W2138064036","doi":"https://doi.org/10.1109/fuzzy.2006.1681994","mag":"2138064036"},"language":"en","primary_location":{"id":"doi:10.1109/fuzzy.2006.1681994","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2006.1681994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Fuzzy 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/A5046054978","display_name":"R. Hassan","orcid":"https://orcid.org/0000-0003-1062-1719"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"R. Hassan","raw_affiliation_strings":["Department of Computer Science and Software Engineering, University of Melbourne, Melbourne, Australia","Univ. of Melbourne, Melbourne"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"Univ. of Melbourne, Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111980276","display_name":"B. Nath","orcid":null},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"B. Nath","raw_affiliation_strings":["Department of Computer Science and Software Engineering, University of Melbourne, Melbourne, Australia","Univ. of Melbourne, Melbourne"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"Univ. of Melbourne, Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025856575","display_name":"Michael Kirley","orcid":"https://orcid.org/0000-0002-6030-858X"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"M. Kirley","raw_affiliation_strings":["Department of Computer Science and Software Engineering, University of Melbourne, Melbourne, Australia","Univ. of Melbourne, Melbourne"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"Univ. of Melbourne, Melbourne","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046054978"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":0.9541,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.75472403,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"4","issue":null,"first_page":"2120","last_page":"2126"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9991000294685364,"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":0.9991000294685364,"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/T10320","display_name":"Neural Networks and Applications","score":0.9976999759674072,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.8327118754386902},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6736642122268677},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5641069412231445},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.549627423286438},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.541060745716095},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.5367860198020935},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5316375494003296},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4679034650325775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4587547779083252},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4576510488986969},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4259951114654541},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4047514498233795},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3711889386177063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31714287400245667},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23719078302383423},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20376232266426086}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8327118754386902},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6736642122268677},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5641069412231445},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.549627423286438},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.541060745716095},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.5367860198020935},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5316375494003296},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4679034650325775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4587547779083252},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4576510488986969},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4259951114654541},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4047514498233795},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3711889386177063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31714287400245667},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23719078302383423},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20376232266426086},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fuzzy.2006.1681994","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2006.1681994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Fuzzy Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:jupiter.its.unimelb.edu.au:11343/31862","is_oa":false,"landing_page_url":"http://hdl.handle.net/11343/31862","pdf_url":null,"source":{"id":"https://openalex.org/S4377196259","display_name":"Minerva Access (University of Melbourne)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165779595","host_organization_name":"The University of Melbourne","host_organization_lineage":["https://openalex.org/I165779595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE International Conference on Fuzzy Systems","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W135851637","https://openalex.org/W1566023464","https://openalex.org/W1870844274","https://openalex.org/W2019207321","https://openalex.org/W2033194777","https://openalex.org/W2079325629","https://openalex.org/W2094631910","https://openalex.org/W2097023393","https://openalex.org/W2104447826","https://openalex.org/W2113076747","https://openalex.org/W2134514463","https://openalex.org/W2146150422","https://openalex.org/W2156019969","https://openalex.org/W2156222099","https://openalex.org/W2159265133","https://openalex.org/W2159749003","https://openalex.org/W2162635690","https://openalex.org/W2169533279"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W2097963413","https://openalex.org/W2025614924","https://openalex.org/W2294335174","https://openalex.org/W3145575561","https://openalex.org/W2995886640","https://openalex.org/W1591475660","https://openalex.org/W2001275470","https://openalex.org/W2164162849"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,15,20,52,81,108],"hidden":[4],"Markov":[5],"model":[6,25,97,104,129],"(HMM)":[7],"based":[8,40],"fuzzy":[9,90],"rule":[10],"extraction":[11],"technique":[12],"for":[13],"predicting":[14],"time":[16,74,113],"series":[17,75],"generated":[18],"by":[19],"chaotic":[21],"dynamical":[22],"system.":[23],"The":[24,99,115],"uses":[26],"three":[27],"sequential":[28],"phases.":[29],"Firstly,":[30],"the":[31,37,42,45,60,69,73,77,88,96,102,126,133],"HMM":[32],"is":[33,56,85,105],"used":[34,57],"to":[35,58,66,87,94,132],"partition":[36],"input":[38],"dataset":[39,110],"on":[41],"ordering":[43],"of":[44,63,101,125],"calculated":[46],"log-likelihood":[47],"values":[48],"(similarity":[49],"measures).":[50],"Then,":[51],"recursive":[53],"top-down":[54],"algorithm":[55],"generate":[59],"minimum":[61],"number":[62],"rules":[64,91],"required":[65],"accurately":[67],"predict":[68],"next":[70],"value":[71],"in":[72,92,122],"using":[76,107],"training":[78],"dataset.":[79],"Finally,":[80],"gradient":[82],"descent":[83],"method":[84],"applied":[86],"extracted":[89],"order":[93],"fine-tune":[95],"parameters.":[98],"performance":[100],"proposed":[103,127],"evaluated":[106],"benchmark":[109],"-the":[111],"Mackey-Glass":[112],"series.":[114],"results":[116],"obtained":[117],"clearly":[118],"demonstrate":[119],"significant":[120],"improvement":[121],"prediction":[123],"capabilities":[124],"HMM-fuzzy":[128],"when":[130],"compared":[131],"other":[134],"techniques.":[135]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
