{"id":"https://openalex.org/W2147989037","doi":"https://doi.org/10.1109/isspit.2010.5711781","title":"Sunspot series prediction using a Multiscale Recurrent Neural Network","display_name":"Sunspot series prediction using a Multiscale Recurrent Neural Network","publication_year":2010,"publication_date":"2010-12-01","ids":{"openalex":"https://openalex.org/W2147989037","doi":"https://doi.org/10.1109/isspit.2010.5711781","mag":"2147989037"},"language":"en","primary_location":{"id":"doi:10.1109/isspit.2010.5711781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspit.2010.5711781","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 10th IEEE International Symposium on Signal Processing and Information Technology","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100439020","display_name":"Tae-Hyun Kim","orcid":"https://orcid.org/0009-0003-3341-4242"},"institutions":[{"id":"https://openalex.org/I89440247","display_name":"Myongji University","ror":"https://ror.org/00s9dpb54","country_code":"KR","type":"education","lineage":["https://openalex.org/I89440247"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Tae-Hyun Kim","raw_affiliation_strings":["Department of Electronics Engineering, Myongji University, Yongin si, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Myongji University, Yongin si, South Korea","institution_ids":["https://openalex.org/I89440247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022326567","display_name":"Dong-Chul Park","orcid":"https://orcid.org/0009-0007-7442-2301"},"institutions":[{"id":"https://openalex.org/I89440247","display_name":"Myongji University","ror":"https://ror.org/00s9dpb54","country_code":"KR","type":"education","lineage":["https://openalex.org/I89440247"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-Chul Park","raw_affiliation_strings":["Department of Electronics Engineering, Myongji University, Yongin si, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Myongji University, Yongin si, South Korea","institution_ids":["https://openalex.org/I89440247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033805053","display_name":"Dong-Min Woo","orcid":null},"institutions":[{"id":"https://openalex.org/I89440247","display_name":"Myongji University","ror":"https://ror.org/00s9dpb54","country_code":"KR","type":"education","lineage":["https://openalex.org/I89440247"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-Min Woo","raw_affiliation_strings":["Department of Electronics Engineering, Myongji University, Yongin si, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Myongji University, Yongin si, South Korea","institution_ids":["https://openalex.org/I89440247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109507437","display_name":"Woong Huh","orcid":null},"institutions":[{"id":"https://openalex.org/I89440247","display_name":"Myongji University","ror":"https://ror.org/00s9dpb54","country_code":"KR","type":"education","lineage":["https://openalex.org/I89440247"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Woong Huh","raw_affiliation_strings":["Department of Electronics Engineering, Myongji University, Yongin si, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Myongji University, Yongin si, South Korea","institution_ids":["https://openalex.org/I89440247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039898922","display_name":"Chung-Hwa Yoon","orcid":null},"institutions":[{"id":"https://openalex.org/I89440247","display_name":"Myongji University","ror":"https://ror.org/00s9dpb54","country_code":"KR","type":"education","lineage":["https://openalex.org/I89440247"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chung-Hwa Yoon","raw_affiliation_strings":["Department of Electronics Engineering, Myongji University, Yongin si, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Myongji University, Yongin si, South Korea","institution_ids":["https://openalex.org/I89440247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081586639","display_name":"Hyen-Ug Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I89440247","display_name":"Myongji University","ror":"https://ror.org/00s9dpb54","country_code":"KR","type":"education","lineage":["https://openalex.org/I89440247"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyen-Ug Kim","raw_affiliation_strings":["Department of Electronics Engineering, Myongji University, Yongin si, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Myongji University, Yongin si, South Korea","institution_ids":["https://openalex.org/I89440247"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007974210","display_name":"Yun\u2010Sik Lee","orcid":"https://orcid.org/0000-0002-9328-8490"},"institutions":[{"id":"https://openalex.org/I4210131650","display_name":"Korea Electronics Technology Institute","ror":"https://ror.org/039k6f508","country_code":"KR","type":"facility","lineage":["https://openalex.org/I2801339556","https://openalex.org/I4210089395","https://openalex.org/I4210131650"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yunsik Lee","raw_affiliation_strings":["System IC Research and Development Division, Korea Electronics and Technology Institute, Songnam, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"System IC Research and Development Division, Korea Electronics and Technology Institute, Songnam, South Korea","institution_ids":["https://openalex.org/I4210131650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8158,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74065655,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"399","last_page":"403"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9933000206947327,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9933000206947327,"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"}},{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9858999848365784,"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":0.9786999821662903,"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/recurrent-neural-network","display_name":"Recurrent neural network","score":0.7940655946731567},{"id":"https://openalex.org/keywords/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.6091355085372925},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5868132710456848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5588932037353516},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5532070994377136},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5254432559013367},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5183711647987366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4397238492965698},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34504491090774536},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34411704540252686}],"concepts":[{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.7940655946731567},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.6091355085372925},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5868132710456848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5588932037353516},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5532070994377136},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5254432559013367},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5183711647987366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4397238492965698},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34504491090774536},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34411704540252686},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isspit.2010.5711781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspit.2010.5711781","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 10th IEEE International Symposium on Signal Processing and Information Technology","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":22,"referenced_works":["https://openalex.org/W1488080865","https://openalex.org/W1535224557","https://openalex.org/W1991728252","https://openalex.org/W2021533878","https://openalex.org/W2026016988","https://openalex.org/W2072219848","https://openalex.org/W2079822331","https://openalex.org/W2098969828","https://openalex.org/W2103917855","https://openalex.org/W2110242546","https://openalex.org/W2111341433","https://openalex.org/W2116943203","https://openalex.org/W2116988482","https://openalex.org/W2119374546","https://openalex.org/W2126701066","https://openalex.org/W2132984323","https://openalex.org/W2158442843","https://openalex.org/W2163556707","https://openalex.org/W2172238182","https://openalex.org/W4254311197","https://openalex.org/W6656975793","https://openalex.org/W6676842417"],"related_works":["https://openalex.org/W2165589608","https://openalex.org/W3093557575","https://openalex.org/W2354231916","https://openalex.org/W3182767856","https://openalex.org/W2162140574","https://openalex.org/W3158157485","https://openalex.org/W2789124470","https://openalex.org/W3000407446","https://openalex.org/W2116531472","https://openalex.org/W2103550798"],"abstract_inverted_index":{"A":[0],"prediction":[1,85],"scheme":[2,26],"for":[3],"sunspot":[4,78],"series":[5,79],"using":[6],"a":[7,36,49,52],"Multiscale":[8],"Bilinear":[9,29,40],"Recurrent":[10,41],"Neural":[11,42,96],"Network":[12,43,97],"(M-BRNN)":[13],"is":[14,27,35,87],"proposed":[15,69,107],"in":[16,24,116],"this":[17,25],"paper.":[18],"The":[19,33,102],"recurrent":[20,30],"neural":[21,31],"network":[22],"adopted":[23],"the":[28,58,65,68,76,83,106,111,119],"network.":[32],"M-BRNN":[34],"combination":[37],"of":[38,67,91,118],"several":[39],"(BRNN)":[44],"models.":[45],"Each":[46],"BRNN":[47],"predicts":[48],"signal":[50],"at":[51],"certain":[53],"resolution":[54],"level":[55],"obtained":[56],"by":[57],"wavelet":[59],"transform.":[60],"In":[61],"order":[62],"to":[63],"evaluate":[64],"performance":[66],"M-BRNN-based":[70,108],"predictor,":[71],"experiments":[72],"are":[73],"conducted":[74],"on":[75],"Wolf":[77],"number":[80],"data":[81],"and":[82,99,113],"resulting":[84],"accuracy":[86],"compared":[88],"with":[89],"those":[90],"conventional":[92],"MultiLayer":[93],"Perceptron":[94],"Type":[95],"(MLPNN)-based":[98],"BRNN-based":[100,114],"predictors.":[101],"results":[103],"show":[104],"that":[105],"predictor":[109],"outperforms":[110],"MLPNN-based":[112],"predictors":[115],"terms":[117],"Normalized":[120],"Mean":[121],"Squared":[122],"Error":[123],"(NMSE).":[124]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
