{"id":"https://openalex.org/W4409868951","doi":"https://doi.org/10.1145/3718751.3718867","title":"Neural Network-based Monitoring and Early Warning Model for Economic Cycle Fluctuations","display_name":"Neural Network-based Monitoring and Early Warning Model for Economic Cycle Fluctuations","publication_year":2024,"publication_date":"2024-11-15","ids":{"openalex":"https://openalex.org/W4409868951","doi":"https://doi.org/10.1145/3718751.3718867"},"language":"en","primary_location":{"id":"doi:10.1145/3718751.3718867","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3718751.3718867","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 Big Data, Artificial Intelligence and Risk Management","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/A5029028619","display_name":"Naifeng Liang","orcid":"https://orcid.org/0000-0003-0626-7278"},"institutions":[{"id":"https://openalex.org/I93477617","display_name":"Huizhou University","ror":"https://ror.org/03q3s7962","country_code":"CN","type":"education","lineage":["https://openalex.org/I93477617"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Naifeng Liang","raw_affiliation_strings":["City College of Huizhou, Huizhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"City College of Huizhou, Huizhou, Guangdong, China","institution_ids":["https://openalex.org/I93477617"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101715893","display_name":"Zhiguo Li","orcid":"https://orcid.org/0000-0002-7608-0815"},"institutions":[{"id":"https://openalex.org/I93477617","display_name":"Huizhou University","ror":"https://ror.org/03q3s7962","country_code":"CN","type":"education","lineage":["https://openalex.org/I93477617"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiguo Li","raw_affiliation_strings":["City College of Huizhou, Huizhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"City College of Huizhou, Huizhou, Guangdong, China","institution_ids":["https://openalex.org/I93477617"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080551640","display_name":"Liudan Zhu","orcid":"https://orcid.org/0000-0001-5109-325X"},"institutions":[{"id":"https://openalex.org/I93477617","display_name":"Huizhou University","ror":"https://ror.org/03q3s7962","country_code":"CN","type":"education","lineage":["https://openalex.org/I93477617"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liudan Zhu","raw_affiliation_strings":["City College of Huizhou, Huizhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"City College of Huizhou, Huizhou, Guangdong, China","institution_ids":["https://openalex.org/I93477617"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012148586","display_name":"Tianyi Liu","orcid":"https://orcid.org/0009-0002-1997-0376"},"institutions":[{"id":"https://openalex.org/I93477617","display_name":"Huizhou University","ror":"https://ror.org/03q3s7962","country_code":"CN","type":"education","lineage":["https://openalex.org/I93477617"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Liu","raw_affiliation_strings":["Huizhou Economic and Polytechnic College, Huizhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Huizhou Economic and Polytechnic College, Huizhou, Guangdong, China","institution_ids":["https://openalex.org/I93477617"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051495132","display_name":"Hongshou Chen","orcid":"https://orcid.org/0009-0004-8444-8909"},"institutions":[{"id":"https://openalex.org/I93477617","display_name":"Huizhou University","ror":"https://ror.org/03q3s7962","country_code":"CN","type":"education","lineage":["https://openalex.org/I93477617"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongshou Chen","raw_affiliation_strings":["Huizhou Economic and Polytechnic College, Huizhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Huizhou Economic and Polytechnic College, Huizhou, Guangdong, China","institution_ids":["https://openalex.org/I93477617"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5029028619"],"corresponding_institution_ids":["https://openalex.org/I93477617"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33567456,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"724","last_page":"728"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11059","display_name":"Market Dynamics and Volatility","score":0.9955999851226807,"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"}},"topics":[{"id":"https://openalex.org/T11059","display_name":"Market Dynamics and Volatility","score":0.9955999851226807,"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"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9922999739646912,"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"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9559999704360962,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/warning-system","display_name":"Warning system","score":0.6996371150016785},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6500324010848999},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5710210800170898},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2770747244358063},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14349991083145142}],"concepts":[{"id":"https://openalex.org/C29825287","wikidata":"https://www.wikidata.org/wiki/Q1427940","display_name":"Warning system","level":2,"score":0.6996371150016785},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6500324010848999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5710210800170898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2770747244358063},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14349991083145142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3718751.3718867","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3718751.3718867","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 Big Data, Artificial Intelligence and Risk Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W3004936781","https://openalex.org/W3198691794","https://openalex.org/W4281552303","https://openalex.org/W4285236917","https://openalex.org/W4288058472","https://openalex.org/W4309269703","https://openalex.org/W4380904445","https://openalex.org/W4386397055"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0,205],"article":[1],"proposes":[2],"an":[3,84],"economic":[4,26,64,68,85,172,233],"cycle":[5,86,234],"fluctuation":[6,87],"monitoring":[7,88,228],"and":[8,20,36,70,89,199,225,229],"early":[9,41,230],"warning":[10,42,90,127,231],"model":[11,55,91,96,110,147,168,222],"based":[12,92,143,221],"on":[13,93,144,169],"LSTM":[14,54,95,109,146,167,220],"(Long":[15],"Short-term":[16],"Memory),":[17],"which":[18],"extracts":[19],"learns":[21],"the":[22,34,40,48,53,59,63,81,94,103,108,121,129,133,138,145,160,166,170,177,186,208,215,219],"deep":[23,29],"features":[24],"of":[25,39,62,83,118,165,193,203,232],"data":[27,105,157,173,217],"through":[28,99],"learning":[30,191],"technology,":[31],"thereby":[32],"improving":[33],"accuracy":[35],"real-time":[37,156],"performance":[38,82,122,179],"model.":[43],"The":[44],"experimental":[45,49],"results":[46],"in":[47,210,227],"stage":[50],"indicate":[51],"that":[52],"can":[56],"effectively":[57],"identify":[58],"turning":[60],"points":[61],"cycle,":[65],"accurately":[66],"predict":[67],"fluctuations,":[69],"provide":[71],"scientific":[72],"decision-making":[73],"basis":[74],"for":[75],"policy":[76],"makers.":[77],"In":[78,102,120,155,176],"this":[79],"study,":[80],"was":[97,148,174,189],"evaluated":[98],"four":[100],"experiments.":[101],"historical":[104],"backtesting":[106],"experiment,":[107],"achieved":[111],"a":[112,190,200],"Root":[113],"Mean":[114],"Square":[115],"Error":[116],"(RMSE)":[117],"0.02.":[119],"comparison":[123,180],"experiment":[124,181],"with":[125],"other":[126,153],"models,":[128],"AUC":[130],"(Area":[131],"Under":[132],"ROC":[134],"Curve)":[135],"value":[136],"under":[137,182],"receiver":[139],"operation":[140],"characteristic":[141],"curve":[142],"0.92,":[149],"significantly":[150],"higher":[151],"than":[152],"models.":[154],"prediction":[158,212],"experiments,":[159],"average":[161],"absolute":[162],"error":[163],"(MAE)":[164],"latest":[171],"0.0112%.":[175],"final":[178],"different":[183],"parameter":[184],"settings,":[185],"optimal":[187],"configuration":[188,206],"rate":[192],"0.001,":[194],"100":[195],"hidden":[196],"layer":[197],"units,":[198],"batch":[201],"size":[202],"64.":[204],"performed":[207],"best":[209],"reducing":[211],"errors.":[213],"From":[214],"above":[216],"conclusions,":[218],"is":[223],"efficient":[224],"practical":[226],"fluctuations.":[235]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
