{"id":"https://openalex.org/W2562500537","doi":"https://doi.org/10.1109/cisis.2016.115","title":"Application of the Artifical Neural Network in Predicting the Direction of Stock Market Index","display_name":"Application of the Artifical Neural Network in Predicting the Direction of Stock Market Index","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2562500537","doi":"https://doi.org/10.1109/cisis.2016.115","mag":"2562500537"},"language":"en","primary_location":{"id":"doi:10.1109/cisis.2016.115","doi":"https://doi.org/10.1109/cisis.2016.115","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisis.2016.115","pdf_url":null,"source":{"id":"https://openalex.org/S4393919748","display_name":"... International Conference on Complex, Intelligent and Software Intensive Systems","issn_l":"2836-8711","issn":["2836-8711"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5057009637","display_name":"Mingyue Qiu","orcid":"https://orcid.org/0000-0002-6670-7194","observed_orcids":["https://orcid.org/0000-0002-6670-7194"]},"institutions":[{"id":"https://openalex.org/I100722782","display_name":"Fukuoka Institute of Technology","ror":"https://ror.org/00bmxak18","country_code":"JP","type":"education","lineage":["https://openalex.org/I100722782"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qiu Mingyue","raw_affiliation_strings":["Department of System Management, Fukuoka Institute of Technology, Fukuoka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of System Management, Fukuoka Institute of Technology, Fukuoka, Japan","institution_ids":["https://openalex.org/I100722782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100753413","display_name":"Li Cheng","orcid":"https://orcid.org/0000-0003-3261-3533","observed_orcids":["https://orcid.org/0000-0003-3261-3533","https://orcid.org/0000-0002-4615-1133"]},"institutions":[{"id":"https://openalex.org/I100722782","display_name":"Fukuoka Institute of Technology","ror":"https://ror.org/00bmxak18","country_code":"JP","type":"education","lineage":["https://openalex.org/I100722782"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Li Cheng","raw_affiliation_strings":["Department of System Management, Fukuoka Institute of Technology, Fukuoka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of System Management, Fukuoka Institute of Technology, Fukuoka, Japan","institution_ids":["https://openalex.org/I100722782"]}]},{"author_position":"last","author":{"id":null,"display_name":"Song Yu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I100722782","display_name":"Fukuoka Institute of Technology","ror":"https://ror.org/00bmxak18","country_code":"JP","type":"education","lineage":["https://openalex.org/I100722782"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Song Yu","raw_affiliation_strings":["Department of System Management, Fukuoka Institute of Technology, Fukuoka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of System Management, Fukuoka Institute of Technology, Fukuoka, Japan","institution_ids":["https://openalex.org/I100722782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I100722782"],"apc_list":null,"apc_paid":null,"fwci":2.1212,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.87485122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"219","last_page":"223"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":1.0,"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":1.0,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.0,"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":0.0,"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/stock-index-forecasting","display_name":"stock index forecasting","score":0.8529999852180481},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.8500000238418579},{"id":"https://openalex.org/keywords/genetic-algorithm-optimization","display_name":"genetic algorithm optimization","score":0.925000011920929},{"id":"https://openalex.org/keywords/japanese-stock-market","display_name":"Japanese stock market","score":0.9259999990463257},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.8230000138282776}],"concepts":[{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.8539853096008301},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.7686491012573242},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6718190908432007},{"id":"https://openalex.org/C88389905","wikidata":"https://www.wikidata.org/wiki/Q223371","display_name":"Stock market index","level":4,"score":0.6435614228248596},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6298125982284546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5801636576652527},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.5508902668952942},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5017807483673096},{"id":"https://openalex.org/C192737826","wikidata":"https://www.wikidata.org/wiki/Q5035802","display_name":"Capitalization-weighted index","level":5,"score":0.43892961740493774},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29945918917655945},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2850200831890106},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16563913226127625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13972333073616028},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08004188537597656},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"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/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisis.2016.115","doi":"https://doi.org/10.1109/cisis.2016.115","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisis.2016.115","pdf_url":null,"source":{"id":"https://openalex.org/S4393919748","display_name":"... International Conference on Complex, Intelligent and Software Intensive Systems","issn_l":"2836-8711","issn":["2836-8711"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1566309885","https://openalex.org/W1586335931","https://openalex.org/W1965062021","https://openalex.org/W1968182870","https://openalex.org/W1971735090","https://openalex.org/W1980836123","https://openalex.org/W1988518729","https://openalex.org/W1990522705","https://openalex.org/W2011909190","https://openalex.org/W2012079387","https://openalex.org/W2017537474","https://openalex.org/W2026477331","https://openalex.org/W2032170121","https://openalex.org/W2049949574","https://openalex.org/W2058417559","https://openalex.org/W2059852492","https://openalex.org/W2063606086","https://openalex.org/W2070181657","https://openalex.org/W2079143456","https://openalex.org/W2122590186","https://openalex.org/W2137983211","https://openalex.org/W2149723649","https://openalex.org/W2154626199","https://openalex.org/W2158663270","https://openalex.org/W2166656061","https://openalex.org/W2166859533","https://openalex.org/W3146803896","https://openalex.org/W4211050817","https://openalex.org/W4241658115","https://openalex.org/W6682939604"],"related_works":["https://openalex.org/W2400770063","https://openalex.org/W6940052898","https://openalex.org/W7024850475","https://openalex.org/W6923580575","https://openalex.org/W3190930981","https://openalex.org/W6902508276","https://openalex.org/W2789399411","https://openalex.org/W3155013200","https://openalex.org/W2032550340","https://openalex.org/W3196022242"],"abstract_inverted_index":{"In":[0,81],"the":[1,13,18,33,36,60,74,77,93,96,108,112,115,120,136,140,143,148,152,163,171,178,187,205,208],"business":[2],"sector,":[3],"it":[4,200],"has":[5],"always":[6],"been":[7],"a":[8,25,194],"difficult":[9],"task":[10],"to":[11,72,91,110,203],"predict":[12,92,111],"exact":[14],"daily":[15,97],"price":[16,40,118,167],"of":[17,28,35,38,76,88,95,104,114,119,139,142,165,207],"stock":[19,39,61,78,98,122,144,166],"market":[20,62,79,99,123,145],"index,":[21],"hence,":[22],"there":[23],"is":[24,107,201],"great":[26],"deal":[27],"research":[29,67],"being":[30],"conducted":[31],"regarding":[32],"prediction":[34,137],"direction":[37,75,94,113,168],"index":[41,124,146],"movement.":[42],"Many":[43],"factors":[44],"such":[45],"as":[46],"political":[47],"events,":[48],"general":[49],"economic":[50],"conditions,":[51],"and":[52,161,175,198],"traders'":[53],"expectations":[54],"may":[55],"have":[56],"an":[57,127],"influence":[58],"on":[59],"index.":[63,80,100],"There":[64],"are":[65],"numerous":[66],"studies":[68],"that":[69,186,199],"use":[70],"indicators":[71],"forecast":[73,196],"this":[82,105],"study,":[83],"we":[84,150],"applied":[85],"two":[86],"types":[87],"input":[89,190],"variables":[90,191],"The":[101],"main":[102],"contribution":[103],"study":[106],"ability":[109],"next":[116],"day's":[117],"Japanese":[121],"by":[125,169],"using":[126,155,170],"optimized":[128,209],"artificial":[129],"neural":[130],"network":[131],"(ANN)":[132],"model.":[133,211],"To":[134],"improve":[135],"accuracy":[138,197],"trend":[141],"in":[147],"future,":[149],"optimize":[151],"ANN":[153,210],"model":[154,174],"genetic":[156],"algorithms":[157],"(GA).":[158],"We":[159],"demonstrate":[160],"verify":[162],"predictability":[164],"hybrid":[172],"GA-ANN":[173],"then":[176],"compare":[177],"performance":[179,206],"with":[180],"prior":[181],"studies.":[182],"Empirical":[183],"results":[184],"show":[185],"Type":[188],"2":[189],"can":[192],"generate":[193],"higher":[195],"possible":[202],"enhance":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":11},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2017-01-06T00:00:00"}