{"id":"https://openalex.org/W3005474981","doi":"https://doi.org/10.1145/3377713.3377744","title":"Time Series Prediction Based on Decomposition and Synthesis","display_name":"Time Series Prediction Based on Decomposition and Synthesis","publication_year":2019,"publication_date":"2019-12-20","ids":{"openalex":"https://openalex.org/W3005474981","doi":"https://doi.org/10.1145/3377713.3377744","mag":"3005474981"},"language":"en","primary_location":{"id":"doi:10.1145/3377713.3377744","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3377713.3377744","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 2nd 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/A5059470482","display_name":"Junguang Li","orcid":null},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junguang Li","raw_affiliation_strings":["Key Laboratory of Computer Vision &amp; System, Ministry of Education, Tianjin University of Technology, Tianjin China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computer Vision &amp; System, Ministry of Education, Tianjin University of Technology, Tianjin China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100917265","display_name":"Shuying Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuying Yang","raw_affiliation_strings":["School of Computer Science and Engineering, Tianjin University of Technology, Tianjin China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Tianjin University of Technology, Tianjin China","institution_ids":["https://openalex.org/I136765683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059470482"],"corresponding_institution_ids":["https://openalex.org/I136765683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.23101738,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"171","last_page":"177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9955000281333923,"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":0.9955000281333923,"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":0.9944999814033508,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9901000261306763,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.7050195932388306},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.6116633415222168},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.593114972114563},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4505676031112671},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3728711009025574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17661237716674805},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.06777414679527283}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.7050195932388306},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.6116633415222168},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.593114972114563},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4505676031112671},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3728711009025574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17661237716674805},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.06777414679527283},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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:10.1145/3377713.3377744","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3377713.3377744","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1854262898","https://openalex.org/W1964000773","https://openalex.org/W1966499742","https://openalex.org/W1980025918","https://openalex.org/W1999933124","https://openalex.org/W2064675550","https://openalex.org/W2117014758","https://openalex.org/W2511197413","https://openalex.org/W2512674116","https://openalex.org/W2553839055","https://openalex.org/W2573587735","https://openalex.org/W2594562288","https://openalex.org/W2797106044","https://openalex.org/W2888788502","https://openalex.org/W2965771385"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"In":[0,102],"recent":[1],"years,":[2],"the":[3,12,16,32,42,45,77,80,88,96,105,114,119,126,134,143,147,154],"deep":[4],"learning":[5],"method":[6,109],"has":[7,28,36],"been":[8],"widely":[9],"used":[10,111],"in":[11,26,39],"financial":[13],"field,":[14],"promoting":[15],"development":[17],"of":[18,91,125,146],"stock":[19],"price":[20],"forecasting.":[21],"The":[22,66,128,138],"time":[23,46,56,67],"series":[24,47,57,68],"data":[25,48],"reality":[27],"complex":[29],"characteristics,":[30],"and":[31,64,87,122],"traditional":[33,155],"single":[34],"model":[35,60,148],"great":[37],"limitations":[38],"prediction.":[40],"For":[41,76],"problem":[43,78],"that":[44,79,142],"is":[49,69,99,110,131,149],"too":[50],"complicated,":[51],"this":[52,103],"paper":[53],"proposes":[54],"a":[55],"mixed":[58],"prediction":[59,89,144],"based":[61],"on":[62],"decomposition":[63,74],"synthesis.":[65],"decomposed":[70,115],"by":[71,133],"empirical":[72],"mode":[73],"(EMD).":[75],"calculation":[81],"complexity":[82,121],"becomes":[83],"larger":[84],"after":[85],"decomposition,":[86],"error":[90,98,124],"each":[92],"sub-component":[93],"leads":[94],"to":[95,112],"total":[97,123],"still":[100],"large.":[101],"paper,":[104],"sampled":[106],"entropy":[107],"(SE)":[108],"combine":[113],"subsequences,":[116],"which":[117],"reduces":[118],"computational":[120],"algorithm.":[127],"combined":[129],"sequence":[130],"predicted":[132],"LSTM":[135],"neural":[136],"network.":[137],"experimental":[139],"result":[140],"show":[141],"accuracy":[145],"significantly":[150],"improved":[151],"compared":[152],"with":[153],"model.":[156]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
