{"id":"https://openalex.org/W2024218705","doi":"https://doi.org/10.1109/icmlc.2014.7009672","title":"A neuro-fuzzy based method for TAIEX forecasting","display_name":"A neuro-fuzzy based method for TAIEX forecasting","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2024218705","doi":"https://doi.org/10.1109/icmlc.2014.7009672","mag":"2024218705"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2014.7009672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2014.7009672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Conference on Machine Learning and Cybernetics","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/A5044493129","display_name":"Zhaoyu Wang","orcid":"https://orcid.org/0009-0009-6892-1264"},"institutions":[{"id":"https://openalex.org/I142974352","display_name":"National Sun Yat-sen University","ror":"https://ror.org/00mjawt10","country_code":"TW","type":"education","lineage":["https://openalex.org/I142974352"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Zhao-Yu Wang","raw_affiliation_strings":["Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan","Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, 80424 Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I142974352"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, 80424 Taiwan","institution_ids":["https://openalex.org/I142974352"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024403730","display_name":"Shie-Jue Lee","orcid":"https://orcid.org/0000-0001-8004-4625"},"institutions":[{"id":"https://openalex.org/I142974352","display_name":"National Sun Yat-sen University","ror":"https://ror.org/00mjawt10","country_code":"TW","type":"education","lineage":["https://openalex.org/I142974352"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shie-Jue Lee","raw_affiliation_strings":["Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan","Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, 80424 Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I142974352"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, 80424 Taiwan","institution_ids":["https://openalex.org/I142974352"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044493129"],"corresponding_institution_ids":["https://openalex.org/I142974352"],"apc_list":null,"apc_paid":null,"fwci":0.4058,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68418386,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"363","issue":null,"first_page":"579","last_page":"584"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T10320","display_name":"Neural Networks and Applications","score":0.9916999936103821,"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":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6796286106109619},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6242266297340393},{"id":"https://openalex.org/keywords/neuro-fuzzy","display_name":"Neuro-fuzzy","score":0.602962851524353},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5435658693313599},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5383961796760559},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5350877642631531},{"id":"https://openalex.org/keywords/fuzzy-rule","display_name":"Fuzzy rule","score":0.5181242823600769},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49433469772338867},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4287252426147461},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.39827021956443787},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2072952389717102},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13107120990753174}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6796286106109619},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6242266297340393},{"id":"https://openalex.org/C29470771","wikidata":"https://www.wikidata.org/wiki/Q4165150","display_name":"Neuro-fuzzy","level":4,"score":0.602962851524353},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5435658693313599},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5383961796760559},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5350877642631531},{"id":"https://openalex.org/C2780049643","wikidata":"https://www.wikidata.org/wiki/Q5511139","display_name":"Fuzzy rule","level":4,"score":0.5181242823600769},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49433469772338867},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4287252426147461},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.39827021956443787},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2072952389717102},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13107120990753174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc.2014.7009672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2014.7009672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Conference on Machine Learning and Cybernetics","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/W1971869067","https://openalex.org/W1993641947","https://openalex.org/W2020820283","https://openalex.org/W2024850745","https://openalex.org/W2025426031","https://openalex.org/W2027182449","https://openalex.org/W2052946472","https://openalex.org/W2059804518","https://openalex.org/W2069454342","https://openalex.org/W2086694651","https://openalex.org/W2098725265","https://openalex.org/W2121565257","https://openalex.org/W2124153830","https://openalex.org/W2127817155","https://openalex.org/W2477834368"],"related_works":["https://openalex.org/W2609187215","https://openalex.org/W3207109968","https://openalex.org/W2133615482","https://openalex.org/W2336148757","https://openalex.org/W1496490105","https://openalex.org/W129092644","https://openalex.org/W81519025","https://openalex.org/W1822436433","https://openalex.org/W1826040410","https://openalex.org/W2114438081"],"abstract_inverted_index":{"Time":[0],"series":[1,28,61],"prediction":[2,147],"can":[3,47,67],"be":[4,48],"widely":[5],"applied":[6],"to":[7,31,38,89,105,145],"a":[8,13,55,91,95,115,121],"variety":[9],"of":[10,15,26,109,138,158],"fields.":[11],"Recently,":[12],"lot":[14],"artificial":[16],"intelligence":[17],"(Al)":[18],"techniques":[19,35],"have":[20],"been":[21],"exploited":[22],"in":[23],"the":[24,72,79,107,110,130,136,139,156,159],"task":[25],"time":[27,60],"prediction.":[29,62],"Compared":[30],"statistical":[32],"methods,":[33],"Al":[34],"are":[36,87,103],"easier":[37],"use":[39],"for":[40,59,148],"real":[41],"world":[42],"data,":[43],"and":[44,101,129],"their":[45],"performance":[46,70],"better.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53],"propose":[54],"neuro-fuzzy":[56,64],"based":[57,65],"system":[58,66,141,161],"The":[63,152],"generate":[68],"superior":[69],"through":[71],"relationship":[73],"among":[74],"different":[75],"features.":[76],"By":[77],"partitioning":[78],"training":[80],"data":[81],"into":[82],"clusters,":[83],"fuzzy":[84,92,96,111],"IF-THEN":[85],"rules":[86],"extracted":[88],"form":[90],"rule-base.":[93],"Then,":[94],"network":[97],"is":[98],"constructed":[99],"accordingly":[100],"parameters":[102],"refined":[104],"increase":[106],"precision":[108],"rule-base":[112],"by":[113,142],"applying":[114,143],"hybrid":[116],"learning":[117],"algorithm":[118],"which":[119],"combines":[120],"recursive":[122],"singular":[123],"value":[124],"decomposition-based":[125],"least":[126],"squares":[127],"estimator":[128],"gradient":[131],"descent":[132],"method.":[133],"We":[134],"demonstrate":[135],"effectiveness":[137],"proposed":[140,160],"it":[144],"do":[146],"TAIEX":[149],"stock":[150],"indices.":[151],"experimental":[153],"results":[154],"conclude":[155],"superiority":[157],"over":[162],"other":[163],"existing":[164],"systems.":[165]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
