{"id":"https://openalex.org/W4388637575","doi":"https://doi.org/10.3390/info14110610","title":"An Integrated Time Series Prediction Model Based on Empirical Mode Decomposition and Two Attention Mechanisms","display_name":"An Integrated Time Series Prediction Model Based on Empirical Mode Decomposition and Two Attention Mechanisms","publication_year":2023,"publication_date":"2023-11-11","ids":{"openalex":"https://openalex.org/W4388637575","doi":"https://doi.org/10.3390/info14110610"},"language":"en","primary_location":{"id":"doi:10.3390/info14110610","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info14110610","pdf_url":"https://www.mdpi.com/2078-2489/14/11/610/pdf?version=1699875458","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/14/11/610/pdf?version=1699875458","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089702415","display_name":"Xianchang Wang","orcid":"https://orcid.org/0000-0001-8775-8188"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianchang Wang","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University, Changchun 130012, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University, Changchun 130012, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061773188","display_name":"Siyu Dong","orcid":"https://orcid.org/0009-0005-9494-783X"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyu Dong","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University, Changchun 130012, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University, Changchun 130012, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100422098","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0002-8597-5813"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun 130012, China"],"raw_orcid":"https://orcid.org/0000-0002-8597-5813","affiliations":[{"raw_affiliation_string":"Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun 130012, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100422098"],"corresponding_institution_ids":["https://openalex.org/I194450716"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":2.2714,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.88275705,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"14","issue":"11","first_page":"610","last_page":"610"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9480999708175659,"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/normalization","display_name":"Normalization (sociology)","score":0.7734320163726807},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.7441080808639526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.689853310585022},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6215612888336182},{"id":"https://openalex.org/keywords/subsequence","display_name":"Subsequence","score":0.6171913743019104},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5433819890022278},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48331403732299805},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.4218844175338745},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4126739203929901},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3943925201892853},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3417893052101135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3398139476776123},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23424288630485535}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7734320163726807},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.7441080808639526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.689853310585022},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6215612888336182},{"id":"https://openalex.org/C137877099","wikidata":"https://www.wikidata.org/wiki/Q1332977","display_name":"Subsequence","level":3,"score":0.6171913743019104},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5433819890022278},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48331403732299805},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.4218844175338745},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4126739203929901},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3943925201892853},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3417893052101135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3398139476776123},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23424288630485535},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info14110610","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info14110610","pdf_url":"https://www.mdpi.com/2078-2489/14/11/610/pdf?version=1699875458","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d3bfe2cbd16b41259bc501e00b81dd6f","is_oa":true,"landing_page_url":"https://doaj.org/article/d3bfe2cbd16b41259bc501e00b81dd6f","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":"Information, Vol 14, Iss 11, p 610 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info14110610","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info14110610","pdf_url":"https://www.mdpi.com/2078-2489/14/11/610/pdf?version=1699875458","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4388637575.pdf"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W2007221293","https://openalex.org/W2064675550","https://openalex.org/W2120390927","https://openalex.org/W2125056386","https://openalex.org/W2604847698","https://openalex.org/W2948517885","https://openalex.org/W2954731415","https://openalex.org/W2973403233","https://openalex.org/W2993122943","https://openalex.org/W2996954980","https://openalex.org/W3008431772","https://openalex.org/W3008931938","https://openalex.org/W3105931142","https://openalex.org/W3117730235","https://openalex.org/W3127809916","https://openalex.org/W3157032429","https://openalex.org/W3159381282","https://openalex.org/W3164310397","https://openalex.org/W3172579827","https://openalex.org/W3177318507","https://openalex.org/W3183845790","https://openalex.org/W3188872815","https://openalex.org/W3212604410","https://openalex.org/W3214199616","https://openalex.org/W4225494949","https://openalex.org/W4226265245","https://openalex.org/W4281611763","https://openalex.org/W4281681455","https://openalex.org/W4283077986","https://openalex.org/W4295575855","https://openalex.org/W4310769220","https://openalex.org/W4312371287","https://openalex.org/W4313472795","https://openalex.org/W4362668568","https://openalex.org/W4377862283","https://openalex.org/W4381736250","https://openalex.org/W6739901393","https://openalex.org/W6764679822","https://openalex.org/W6771626834"],"related_works":["https://openalex.org/W2081563414","https://openalex.org/W2363056446","https://openalex.org/W2359718298","https://openalex.org/W2377062149","https://openalex.org/W3014107421","https://openalex.org/W2076661204","https://openalex.org/W2380939102","https://openalex.org/W1915398038","https://openalex.org/W155406958","https://openalex.org/W4387088901"],"abstract_inverted_index":{"In":[0],"the":[1,36,64,124,141,179],"prediction":[2,22,52,125,143],"of":[3,38,66,127,158,170],"time":[4,50],"series,":[5],"Empirical":[6],"Mode":[7],"Decomposition":[8],"(EMD)":[9],"generates":[10],"subsequences":[11,39,75],"and":[12,57,70,105,129,135],"separates":[13],"short-term":[14],"tendencies":[15],"from":[16,77],"long-term":[17],"ones.":[18],"However,":[19],"a":[20,154],"single":[21,89],"model,":[23],"including":[24],"attention":[25,42,59,119,122,152,171],"mechanism,":[26,43],"has":[27,85],"varying":[28],"effects":[29],"on":[30,54,83,110],"each":[31],"subsequence.":[32],"To":[33],"accurately":[34],"capture":[35],"regularities":[37],"using":[40,74],"an":[41,46],"we":[44],"propose":[45],"integrated":[47,148],"model":[48,62,149],"for":[49,187],"series":[51,90,96,132,177],"based":[53],"signal":[55],"decomposition":[56],"two":[58,99],"mechanisms.":[60,172],"This":[61],"combines":[63],"results":[65,109],"three":[67],"networks\u2014LSTM,":[68],"LSTM-self-attention,":[69],"LSTM-temporal":[71],"attention\u2014all":[72],"trained":[73],"obtained":[76],"EMD.":[78],"Additionally,":[79],"since":[80],"previous":[81],"research":[82],"EMD":[84],"been":[86],"limited":[87],"to":[88,116,164,184],"analysis,":[91],"this":[92],"paper":[93],"includes":[94],"multiple":[95,176],"by":[97,133,145],"employing":[98],"data":[100],"pre-processing":[101],"methods:":[102],"\u2018overall":[103],"normalization\u2019":[104],"\u2018respective":[106],"normalization\u2019.":[107],"Experimental":[108],"various":[111],"datasets":[112],"demonstrate":[113],"that":[114,185],"compared":[115,163],"models":[117,165],"without":[118],"mechanisms,":[120],"temporal":[121,151],"improves":[123],"accuracy":[126],"short-":[128],"medium-term":[130],"decomposed":[131],"15~28%":[134],"45~72%,":[136],"respectively;":[137],"furthermore,":[138],"it":[139],"reduces":[140],"overall":[142],"error":[144,157],"10~17%.":[146],"The":[147],"with":[150],"achieves":[153],"reduction":[155],"in":[156],"approximately":[159],"0.3%,":[160],"primarily":[161],"when":[162],"utilizing":[166],"only":[167],"general":[168],"forms":[169],"Moreover,":[173],"after":[174],"normalizing":[175],"separately,":[178],"predictive":[180],"performance":[181],"is":[182],"equivalent":[183],"achieved":[186],"individual":[188],"series.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-23T08:51:43.019350","created_date":"2025-10-10T00:00:00"}