{"id":"https://openalex.org/W2001086848","doi":"https://doi.org/10.1109/isccsp.2014.6877938","title":"A hybrid method for time series prediction using EMD and SVR","display_name":"A hybrid method for time series prediction using EMD and SVR","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2001086848","doi":"https://doi.org/10.1109/isccsp.2014.6877938","mag":"2001086848"},"language":"en","primary_location":{"id":"doi:10.1109/isccsp.2014.6877938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isccsp.2014.6877938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)","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/A5067430595","display_name":"Bahad\u0131r Bican","orcid":null},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Bahadir Bican","raw_affiliation_strings":["Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey","Dept. of Comput. Eng., Istanbul Tech. Univ., Istanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey","institution_ids":["https://openalex.org/I48912391"]},{"raw_affiliation_string":"Dept. of Comput. Eng., Istanbul Tech. Univ., Istanbul, Turkey","institution_ids":["https://openalex.org/I48912391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040016964","display_name":"Yusuf Yaslan","orcid":"https://orcid.org/0000-0001-8038-948X"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Yusuf Yaslan","raw_affiliation_strings":["Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey","Dept. of Comput. Eng., Istanbul Tech. Univ., Istanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey","institution_ids":["https://openalex.org/I48912391"]},{"raw_affiliation_string":"Dept. of Comput. Eng., Istanbul Tech. Univ., Istanbul, Turkey","institution_ids":["https://openalex.org/I48912391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067430595"],"corresponding_institution_ids":["https://openalex.org/I48912391"],"apc_list":null,"apc_paid":null,"fwci":1.4874,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.84264261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"566","last_page":"569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":1.0,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9968000054359436,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8449361324310303},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8024199604988098},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6984925270080566},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5592039823532104},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.5556073784828186},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.47757747769355774},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.47051018476486206},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4619254469871521},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.44561105966567993},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4193773865699768},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.41140875220298767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39026910066604614},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.389897882938385},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3593946695327759},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35029593110084534},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12831264734268188},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12604591250419617},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09951037168502808},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07883909344673157}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8449361324310303},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8024199604988098},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6984925270080566},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5592039823532104},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.5556073784828186},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.47757747769355774},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.47051018476486206},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4619254469871521},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.44561105966567993},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4193773865699768},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.41140875220298767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39026910066604614},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.389897882938385},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3593946695327759},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35029593110084534},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12831264734268188},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12604591250419617},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09951037168502808},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07883909344673157},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/isccsp.2014.6877938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isccsp.2014.6877938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:polen.itu.edu.tr:11527/63596","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/63596","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.4699999988079071,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1984452465","https://openalex.org/W1991261837","https://openalex.org/W2007221293","https://openalex.org/W2095071330","https://openalex.org/W2126320149","https://openalex.org/W2156909104","https://openalex.org/W2168138569"],"related_works":["https://openalex.org/W3195168932","https://openalex.org/W1996541855","https://openalex.org/W3015453784","https://openalex.org/W2390299251","https://openalex.org/W2121393587","https://openalex.org/W2545045944","https://openalex.org/W2391611294","https://openalex.org/W1585329223","https://openalex.org/W2353181520","https://openalex.org/W2357171463"],"abstract_inverted_index":{"Forecasting":[0],"in":[1],"several":[2],"areas":[3],"such":[4],"as":[5],"stock":[6],"price,":[7],"electricity":[8,54],"power":[9],"consumption,":[10],"tourist":[11],"arrival":[12],"rates":[13],"or":[14,28,38],"capacity":[15],"planning":[16],"allows":[17],"us":[18],"to":[19,48],"give":[20],"decisions":[21],"for":[22],"future":[23],"events.":[24],"The":[25],"rising":[26],"up":[27],"falling":[29],"down":[30],"of":[31,53],"the":[32,50,59,68,91,96],"values":[33],"can":[34],"support":[35],"researchers,":[36],"economists":[37],"investors":[39],"while":[40],"giving":[41],"their":[42],"important":[43],"decisions.":[44],"This":[45],"study":[46],"aims":[47],"forecast":[49],"directional":[51],"movements":[52],"load":[55,63],"demands":[56],"and":[57,74,108],"evaluates":[58],"performance":[60,99],"on":[61,100],"3":[62],"datasets.":[64],"In":[65],"experimental":[66],"results,":[67],"proposed":[69,92],"Empirical":[70],"Mode":[71],"Decomposition":[72],"(EMD)":[73],"Support":[75],"Vector":[76],"Regression":[77],"(SVR)":[78],"based":[79],"hybrid":[80],"method":[81,94],"is":[82,88],"compared":[83],"with":[84],"single":[85,97],"SVR.":[86],"It":[87],"observed":[89],"that":[90],"EMD-SVR":[93],"outperforms":[95],"SVR":[98],"direction":[101],"measurements":[102],"including":[103],"Direction":[104],"Accuracy,":[105],"Correct":[106,109],"Up":[107],"Down":[110],"trends.":[111]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}