{"id":"https://openalex.org/W4214750199","doi":"https://doi.org/10.1145/3508546.3508621","title":"MulRNN: An Enhanced Technique of Multi-Stage-Attention Network for Complex Time Series Prediction","display_name":"MulRNN: An Enhanced Technique of Multi-Stage-Attention Network for Complex Time Series Prediction","publication_year":2021,"publication_date":"2021-12-22","ids":{"openalex":"https://openalex.org/W4214750199","doi":"https://doi.org/10.1145/3508546.3508621"},"language":"en","primary_location":{"id":"doi:10.1145/3508546.3508621","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3508546.3508621","pdf_url":null,"source":{"id":"https://openalex.org/S4363608505","display_name":"2021 4th International Conference on Algorithms, Computing and Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th International Conference on Algorithms, Computing and Artificial Intelligence","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/A5100619058","display_name":"Wenliang Wang","orcid":"https://orcid.org/0000-0002-3894-2357"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenliang Wang","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100651301","display_name":"Jing Li","orcid":"https://orcid.org/0000-0001-5664-9907"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060576992","display_name":"Hanyu Rao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hanyu Rao","raw_affiliation_strings":["Information and Communication Company of State Grid Zhejiang Electric Power Company, China"],"affiliations":[{"raw_affiliation_string":"Information and Communication Company of State Grid Zhejiang Electric Power Company, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072702653","display_name":"Dong Mao","orcid":"https://orcid.org/0000-0002-5744-6316"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong Mao","raw_affiliation_strings":["Information and Communication Company of State Grid Zhejiang Electric Power Company, China"],"affiliations":[{"raw_affiliation_string":"Information and Communication Company of State Grid Zhejiang Electric Power Company, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100619058"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29411765,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994999766349792,"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":0.9994999766349792,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9929999709129333,"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":0.787018895149231},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7428749799728394},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6999484896659851},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6870599985122681},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6755681037902832},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6702746748924255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5918605327606201},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5293579697608948},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5254660844802856},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5045212507247925},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4617476761341095},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43947386741638184},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.4266703426837921},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3941959738731384},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.1694590449333191},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08118194341659546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.787018895149231},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7428749799728394},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6999484896659851},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6870599985122681},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6755681037902832},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6702746748924255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5918605327606201},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5293579697608948},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5254660844802856},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5045212507247925},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4617476761341095},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43947386741638184},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.4266703426837921},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3941959738731384},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.1694590449333191},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08118194341659546},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3508546.3508621","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3508546.3508621","pdf_url":null,"source":{"id":"https://openalex.org/S4363608505","display_name":"2021 4th International Conference on Algorithms, Computing and Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th International Conference on Algorithms, Computing and Artificial Intelligence","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":10,"referenced_works":["https://openalex.org/W2107878631","https://openalex.org/W2172073485","https://openalex.org/W2604847698","https://openalex.org/W2751125473","https://openalex.org/W3015379812","https://openalex.org/W6600373357","https://openalex.org/W6600599538","https://openalex.org/W6603143895","https://openalex.org/W6608384827","https://openalex.org/W6677096361"],"related_works":["https://openalex.org/W3175321409","https://openalex.org/W4312561791","https://openalex.org/W2389894046","https://openalex.org/W2215717369","https://openalex.org/W2146461990","https://openalex.org/W4312309719","https://openalex.org/W4391216528","https://openalex.org/W2980748541","https://openalex.org/W4399581288","https://openalex.org/W4313123484"],"abstract_inverted_index":{"Multivariate":[0],"time":[1,31,59,89,120,167],"series":[2,60,168],"prediction":[3,28,43,63,80],"is":[4,20],"still":[5,21],"playing":[6],"an":[7],"important":[8],"role":[9],"in":[10,164],"many":[11],"fields":[12],"such":[13],"as":[14],"finance,":[15],"transportation":[16],"and":[17,61,87,98,111,148,151],"energy.":[18],"It":[19],"a":[22,41,72],"challenging":[23],"work":[24],"to":[25,103,115,130],"make":[26],"long-term":[27,117],"of":[29,64,119,136,166],"multivariate":[30],"series.":[32,90,121],"The":[33],"existing":[34],"traditional":[35,127],"methods":[36,163],"based":[37,81],"on":[38,82,146],"statistics":[39],"have":[40],"good":[42],"effect":[44],"for":[45,77],"the":[46,54,62,126,132,137],"periodic":[47],"data,":[48],"but":[49],"they":[50],"can":[51],"not":[52],"capture":[53],"complex":[55,78],"dependence":[56],"between":[57,109],"multiple":[58],"long":[65],"term.":[66],"In":[67,122],"this":[68],"paper,":[69],"we":[70,124,141],"propose":[71],"new":[73],"deep":[74],"learning":[75],"framework":[76],"sequence":[79],"multi-stage":[83],"attentions,":[84],"especially":[85],"dynamic":[86],"non-periodic":[88],"MulRNN":[91],"(Multi-Stage-Attention-RNN)":[92],"uses":[93],"convolutional":[94],"neural":[95,100,138],"network":[96,101],"(CNN)":[97],"recurrent":[99],"(RNN)":[102],"extract":[104],"short-term":[105],"locally":[106],"dependent":[107],"patterns":[108,118],"variables,":[110],"introduces":[112],"attention":[113],"mechanisms":[114],"discover":[116],"addition,":[123],"use":[125],"autoregressive":[128],"model":[129,145],"solve":[131],"scale":[133],"insensitivity":[134],"problem":[135],"network.":[139],"Finally,":[140],"validate":[142],"our":[143,152],"proposed":[144],"financial":[147],"energy":[149],"datasets,":[150],"method":[153],"(MulRNN)":[154],"achieves":[155],"significant":[156],"performance":[157],"improvements":[158],"over":[159],"several":[160],"advanced":[161],"baseline":[162],"terms":[165],"prediction.":[169]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}