{"id":"https://openalex.org/W4403717337","doi":"https://doi.org/10.1145/3690407.3690554","title":"Time Series Modeling of the Relationship between Low Turnover Stocks and SSE Index Based on Neural Network","display_name":"Time Series Modeling of the Relationship between Low Turnover Stocks and SSE Index Based on Neural Network","publication_year":2024,"publication_date":"2024-06-21","ids":{"openalex":"https://openalex.org/W4403717337","doi":"https://doi.org/10.1145/3690407.3690554"},"language":"en","primary_location":{"id":"doi:10.1145/3690407.3690554","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3690407.3690554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms","raw_type":"proceedings-article"},"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/A5064399103","display_name":"Xinming Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinming Ma","raw_affiliation_strings":["College of Liberal Arts, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA"],"raw_orcid":"https://orcid.org/0009-0003-0764-0676","affiliations":[{"raw_affiliation_string":"College of Liberal Arts, University of Minnesota, Twin Cities, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"]}]},{"author_position":"last","author":{"id":null,"display_name":"Haoyang Wang","orcid":"https://orcid.org/0009-0008-6510-4819"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyang Wang","raw_affiliation_strings":["Swinburne College, Shandong University of Science and Technology, Jinan, Shandong, China"],"raw_orcid":"https://orcid.org/0009-0008-6510-4819","affiliations":[{"raw_affiliation_string":"Swinburne College, Shandong University of Science and Technology, Jinan, Shandong, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"885","last_page":"889"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.9763000011444092,"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/T12368","display_name":"Grey System Theory Applications","score":0.9763000011444092,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9585999846458435,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9315999746322632,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.6759647130966187},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.653666615486145},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6217375993728638},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5296202301979065},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.48799389600753784},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.34229302406311035},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3064548969268799},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2196561098098755},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2001495659351349},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10876843333244324}],"concepts":[{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.6759647130966187},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.653666615486145},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6217375993728638},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5296202301979065},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.48799389600753784},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34229302406311035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3064548969268799},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2196561098098755},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2001495659351349},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10876843333244324},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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:10.1145/3690407.3690554","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3690407.3690554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2884585870","https://openalex.org/W2964199361","https://openalex.org/W4205507482","https://openalex.org/W4226254316","https://openalex.org/W4293238957"],"related_works":["https://openalex.org/W1919101720","https://openalex.org/W4390822878","https://openalex.org/W96888382","https://openalex.org/W4386126592","https://openalex.org/W2041308758","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W3146111732","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Because":[0],"SSE":[1,26,47,53,70],"index":[2],"plays":[3],"an":[4,15],"important":[5,20],"role":[6],"in":[7,28],"understanding":[8],"and":[9,85,94,108,124],"analyzing":[10],"the":[11,23,29,41,45,52,65,96,105,111,117],"stock":[12],"market,":[13],"as":[14,40],"investor,":[16],"it":[17],"is":[18,55,90],"really":[19],"to":[21,43],"know":[22],"trend":[24,50,71],"of":[25,51,102],"Index":[27,54],"future.":[30],"In":[31],"this":[32],"paper,":[33],"low":[34],"turnover":[35],"rate":[36],"stocks":[37],"are":[38],"chosen":[39],"basis":[42],"predict":[44],"future":[46],"Index.":[48],"The":[49],"divided":[56],"into":[57],"five":[58],"categories":[59],"using":[60],"K-Means":[61],"Algorithm":[62],"based":[63,74],"on":[64,75],"past":[66],"data.":[67],"A":[68],"five-category":[69],"prediction":[72],"model":[73,97,118],"Temporal":[76],"Convolutional":[77,80],"Network":[78],"(TCN),":[79],"Block":[81],"Attention":[82],"Module":[83],"(CBAM)":[84],"Gated":[86],"Recurrent":[87],"Unit":[88],"(GRU)":[89],"proposed.":[91],"After":[92],"training":[93,106],"testing,":[95],"has":[98,119,125],"a":[99,120],"classification":[100],"accuracy":[101,123],"91.35%":[103],"for":[104,110],"set":[107],"83.75%":[109],"test":[112],"set.":[113],"Experiments":[114],"show":[115],"that":[116],"relatively":[121],"high":[122],"certain":[126],"practical":[127],"value.":[128]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}