{"id":"https://openalex.org/W2946977658","doi":"https://doi.org/10.1109/access.2019.2919189","title":"Novel Financial Capital Flow Forecast Framework Using Time Series Theory and Deep Learning: A Case Study Analysis of Yu\u2019e Bao Transaction Data","display_name":"Novel Financial Capital Flow Forecast Framework Using Time Series Theory and Deep Learning: A Case Study Analysis of Yu\u2019e Bao Transaction Data","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2946977658","doi":"https://doi.org/10.1109/access.2019.2919189","mag":"2946977658"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2919189","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919189","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723033.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723033.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068779036","display_name":"Xiaoxian Yang","orcid":"https://orcid.org/0000-0002-0945-4194"},"institutions":[{"id":"https://openalex.org/I135905480","display_name":"Shanghai Polytechnic University","ror":"https://ror.org/02as5yg64","country_code":"CN","type":"education","lineage":["https://openalex.org/I135905480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxian Yang","raw_affiliation_strings":["School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, China","institution_ids":["https://openalex.org/I135905480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008753514","display_name":"Shunyi Mao","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunyi Mao","raw_affiliation_strings":["Computing Center, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computing Center, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087225784","display_name":"Honghao Gao","orcid":"https://orcid.org/0000-0001-6861-9684"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honghao Gao","raw_affiliation_strings":["Computing Center, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-6861-9684","affiliations":[{"raw_affiliation_string":"Computing Center, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029925325","display_name":"Yucong Duan","orcid":"https://orcid.org/0000-0001-8417-892X"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yucong Duan","raw_affiliation_strings":["College of Information Science and Technology, Hainan University, Haikou, China"],"raw_orcid":"https://orcid.org/0000-0001-8417-892X","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Hainan University, Haikou, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113911752","display_name":"Qiming Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089783","display_name":"Shanghai Medical Information Center","ror":"https://ror.org/007wz9933","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210089783"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiming Zou","raw_affiliation_strings":["Shanghai Shangda Hairun Information System Co., Ltd., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Shangda Hairun Information System Co., Ltd., Shanghai, China","institution_ids":["https://openalex.org/I4210089783"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.559,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.92805427,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"70662","last_page":"70672"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9912999868392944,"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":0.9907000064849854,"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/computer-science","display_name":"Computer science","score":0.5779097080230713},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.5492963790893555},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.5213083624839783},{"id":"https://openalex.org/keywords/market-liquidity","display_name":"Market liquidity","score":0.5210870504379272},{"id":"https://openalex.org/keywords/cash-flow","display_name":"Cash flow","score":0.5049083828926086},{"id":"https://openalex.org/keywords/partial-autocorrelation-function","display_name":"Partial autocorrelation function","score":0.4720630943775177},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4717061221599579},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.45033955574035645},{"id":"https://openalex.org/keywords/investment","display_name":"Investment (military)","score":0.41260573267936707},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3926754295825958},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.3736916780471802},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.3553970456123352},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.3494059145450592},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2692813277244568},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1561058759689331},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13898488879203796},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09149664640426636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5779097080230713},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.5492963790893555},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.5213083624839783},{"id":"https://openalex.org/C183582576","wikidata":"https://www.wikidata.org/wiki/Q184783","display_name":"Market liquidity","level":2,"score":0.5210870504379272},{"id":"https://openalex.org/C163428354","wikidata":"https://www.wikidata.org/wiki/Q1047513","display_name":"Cash flow","level":2,"score":0.5049083828926086},{"id":"https://openalex.org/C114775468","wikidata":"https://www.wikidata.org/wiki/Q1258253","display_name":"Partial autocorrelation function","level":4,"score":0.4720630943775177},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4717061221599579},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.45033955574035645},{"id":"https://openalex.org/C27548731","wikidata":"https://www.wikidata.org/wiki/Q88272","display_name":"Investment (military)","level":3,"score":0.41260573267936707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3926754295825958},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3736916780471802},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3553970456123352},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3494059145450592},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2692813277244568},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1561058759689331},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13898488879203796},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09149664640426636},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2919189","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919189","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723033.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:64b2981f84f7485fbbbc0f924aa075d8","is_oa":true,"landing_page_url":"https://doaj.org/article/64b2981f84f7485fbbbc0f924aa075d8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 70662-70672 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2919189","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919189","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723033.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G788056237","display_name":null,"funder_award_id":"EGD18XQD01","funder_id":"https://openalex.org/F4320329022","funder_display_name":"Shanghai Polytechnic University"},{"id":"https://openalex.org/G8898318021","display_name":null,"funder_award_id":"61502294","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329022","display_name":"Shanghai Polytechnic University","ror":"https://ror.org/02as5yg64"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2946977658.pdf","grobid_xml":"https://content.openalex.org/works/W2946977658.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W569169453","https://openalex.org/W1785967024","https://openalex.org/W1994440344","https://openalex.org/W2024760831","https://openalex.org/W2046794274","https://openalex.org/W2080443573","https://openalex.org/W2122410182","https://openalex.org/W2184207288","https://openalex.org/W2297152540","https://openalex.org/W2311599690","https://openalex.org/W2343644403","https://openalex.org/W2438521089","https://openalex.org/W2524922919","https://openalex.org/W2575700785","https://openalex.org/W2597866042","https://openalex.org/W2621438471","https://openalex.org/W2624385633","https://openalex.org/W2695427614","https://openalex.org/W2722632382","https://openalex.org/W2737551799","https://openalex.org/W2759764766","https://openalex.org/W2770001439","https://openalex.org/W2770354671","https://openalex.org/W2773049109","https://openalex.org/W2781966338","https://openalex.org/W2792061194","https://openalex.org/W2802914173","https://openalex.org/W2887263516","https://openalex.org/W2891182845","https://openalex.org/W2891812095","https://openalex.org/W2897938066","https://openalex.org/W2904081210","https://openalex.org/W2913083325","https://openalex.org/W2926247598","https://openalex.org/W2930749509","https://openalex.org/W2963122061","https://openalex.org/W2963446712","https://openalex.org/W2991061473","https://openalex.org/W3122093417","https://openalex.org/W3125973117","https://openalex.org/W3164159616","https://openalex.org/W6744953002","https://openalex.org/W6756710378","https://openalex.org/W6771761221"],"related_works":["https://openalex.org/W4253828147","https://openalex.org/W2566735280","https://openalex.org/W4238864106","https://openalex.org/W2000117560","https://openalex.org/W2565406980","https://openalex.org/W2916191650","https://openalex.org/W1975547340","https://openalex.org/W2376930070","https://openalex.org/W122567830","https://openalex.org/W4312557201"],"abstract_inverted_index":{"Appropriate":[0],"monetary":[1],"liquidity":[2],"is":[3,40,72,93,109,136,157],"important":[4],"for":[5,14,64],"financial":[6,66,74],"institutions.":[7],"When":[8],"institutions":[9],"lack":[10],"adequate":[11],"cash":[12,39],"flow":[13],"customer":[15],"redemption,":[16],"their":[17,21],"income":[18],"will":[19,23],"decrease,":[20],"reputation":[22],"be":[24],"affected,":[25],"and":[26,116,172,181,188,202],"they":[27],"may":[28,44],"even":[29],"go":[30],"bankrupt.":[31],"However,":[32],"the":[33,80,95,113,125,140,143,161,194],"opposite":[34],"extreme":[35],"in":[36,46,98],"which":[37,71,121],"more":[38],"reserved":[41],"than":[42],"needed":[43],"result":[45],"lost":[47],"opportunities":[48],"to":[49,60,87,138,159,191],"make":[50],"successful":[51],"investments.":[52],"This":[53,165],"study":[54],"uses":[55],"Yu'e":[56,69,99],"Bao":[57],"transaction":[58,148],"data":[59],"investigate":[61],"a":[62,73,104,130,151,169,177,206],"method":[63,154],"forecasting":[65],"capital":[67,221],"flow.":[68],"Bao,":[70],"product":[75],"launched":[76],"by":[77,111,124],"Alibaba,":[78],"faces":[79],"core":[81],"challenge":[82],"of":[83,142,179,200,208],"maximizing":[84],"commercial":[85],"profits":[86],"reduce":[88],"investment":[89,101],"risks.":[90],"Liquidity":[91],"risk":[92],"considered":[94],"main":[96],"factor":[97],"Bao's":[100],"strategy.":[102],"First,":[103],"linear":[105,170],"model":[106,133,144,166,196],"called":[107,134,155],"YEB_ARIMA":[108],"proposed":[110,213],"determining":[112],"autocorrelation":[114,118],"(ACF)":[115],"partial":[117],"(PACF)":[119],"parameters,":[120],"are":[122,183,217],"optimized":[123],"grid":[126],"search":[127],"method.":[128],"Second,":[129],"deep":[131],"learning":[132,153],"YEB_LSTM":[135],"introduced":[137],"strengthen":[139],"expressiveness":[141],"that":[145,193],"yields":[146],"nonlinear":[147],"features.":[149],"Then,":[150],"hybrid":[152,195],"YEB_Hybrid":[156],"applied":[158],"improve":[160],"original":[162],"weak":[163],"classifiers.":[164],"includes":[167],"both":[168],"combination":[171],"logistic":[173],"regression":[174],"learning.":[175],"Third,":[176],"set":[178],"experiments":[180],"analyses":[182],"conducted":[184],"based":[185,219],"on":[186,220],"subscription":[187],"redemption":[189],"datasets":[190],"demonstrate":[192],"achieves":[197],"an":[198],"accuracy":[199],"84.39%":[201],"84.36%,":[203],"respectively,":[204],"under":[205],"variety":[207],"evaluation":[209],"indexes.":[210],"Finally,":[211],"various":[212],"fund":[214],"reserve":[215],"ratios":[216],"provided":[218],"forecasts.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
