{"id":"https://openalex.org/W2885642955","doi":"https://doi.org/10.1109/access.2018.2864222","title":"Spectrum Prediction Based on Taguchi Method in Deep Learning With Long Short-Term Memory","display_name":"Spectrum Prediction Based on Taguchi Method in Deep Learning With Long Short-Term Memory","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2885642955","doi":"https://doi.org/10.1109/access.2018.2864222","mag":"2885642955"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2864222","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2864222","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2864222","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041183487","display_name":"Ling Yu","orcid":"https://orcid.org/0000-0002-0139-0966"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Yu","raw_affiliation_strings":["College of Communications Engineering, Army Engineering University of PLA, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Communications Engineering, Army Engineering University of PLA, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089564180","display_name":"Jin Chen","orcid":"https://orcid.org/0000-0002-6497-4141"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Chen","raw_affiliation_strings":["College of Communications Engineering, Army Engineering University of PLA, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Communications Engineering, Army Engineering University of PLA, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076455133","display_name":"Guoru Ding","orcid":"https://orcid.org/0000-0003-1780-2547"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoru Ding","raw_affiliation_strings":["College of Communications Engineering, Army Engineering University of PLA, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-1780-2547","affiliations":[{"raw_affiliation_string":"College of Communications Engineering, Army Engineering University of PLA, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057166109","display_name":"Ya Tu","orcid":"https://orcid.org/0000-0001-5081-5329"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ya Tu","raw_affiliation_strings":["College of Information and Communication, Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Communication, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101744547","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0002-2849-4888"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yang","raw_affiliation_strings":["The 63rd Institute, National University of Defense Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-2849-4888","affiliations":[{"raw_affiliation_string":"The 63rd Institute, National University of Defense Technology, Nanjing, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067053704","display_name":"Jiachen Sun","orcid":"https://orcid.org/0000-0002-4042-1200"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiachen Sun","raw_affiliation_strings":["College of Communications Engineering, Army Engineering University of PLA, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Communications Engineering, Army Engineering University of PLA, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":7.5389,"has_fulltext":false,"cited_by_count":100,"citation_normalized_percentile":{"value":0.97991019,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"45923","last_page":"45933"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9977999925613403,"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/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.8158239126205444},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7403435707092285},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6608179807662964},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5781804919242859},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5498341917991638},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5198362469673157},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47896531224250793},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39671894907951355},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3201158344745636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8158239126205444},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7403435707092285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6608179807662964},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5781804919242859},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5498341917991638},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5198362469673157},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47896531224250793},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39671894907951355},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3201158344745636}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2864222","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2864222","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a55252bdedf24a498ab4733a0f7ffcef","is_oa":true,"landing_page_url":"https://doaj.org/article/a55252bdedf24a498ab4733a0f7ffcef","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":"IEEE Access, Vol 6, Pp 45923-45933 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2864222","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2864222","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2871462706","display_name":null,"funder_award_id":"61501510","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G381434843","display_name":"\u5e7f\u57df\u52a8\u6001\u9891\u8c31\u6001\u52bf\u57fa\u7840\u7406\u8bba\u4e0e\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61631020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4410762970","display_name":null,"funder_award_id":"BK20150717","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G490208846","display_name":null,"funder_award_id":"2018T110426","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G8145678639","display_name":"\u65e0\u4eba\u673a\u901a\u4fe1\u7f51\u7edc\u4e2d\u7a33\u5065\u9891\u8c31\u5171\u4eab\u7406\u8bba\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61871398","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W356062350","https://openalex.org/W1488270586","https://openalex.org/W1526055535","https://openalex.org/W1878059963","https://openalex.org/W1968490445","https://openalex.org/W1987615181","https://openalex.org/W2012080288","https://openalex.org/W2036931385","https://openalex.org/W2060135116","https://openalex.org/W2064675550","https://openalex.org/W2066757459","https://openalex.org/W2110798624","https://openalex.org/W2111136196","https://openalex.org/W2117922789","https://openalex.org/W2126320149","https://openalex.org/W2149572366","https://openalex.org/W2155999145","https://openalex.org/W2157543034","https://openalex.org/W2169223481","https://openalex.org/W2213037223","https://openalex.org/W2504266609","https://openalex.org/W2583684860","https://openalex.org/W2593438634","https://openalex.org/W2607059137","https://openalex.org/W2734408173","https://openalex.org/W2741051040","https://openalex.org/W2744822029","https://openalex.org/W2755056899","https://openalex.org/W2756144809","https://openalex.org/W2766363275","https://openalex.org/W2772526503","https://openalex.org/W2793198093","https://openalex.org/W2795250443","https://openalex.org/W2919115771","https://openalex.org/W2962740129","https://openalex.org/W2962883549","https://openalex.org/W2963601182","https://openalex.org/W2963889719","https://openalex.org/W3011621684","https://openalex.org/W4234543771","https://openalex.org/W6612102294","https://openalex.org/W6631321124","https://openalex.org/W6742049128"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W2076543106","https://openalex.org/W3158157485","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2789124470","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W3000407446"],"abstract_inverted_index":{"Spectrum":[0],"prediction":[1,25,76,152,175,192],"is":[2,200,219],"a":[3,74,79],"promising":[4],"technology":[5],"in":[6,19,54,227],"cognitive":[7],"radio":[8],"networks,":[9],"since":[10],"it":[11],"can":[12],"reduce":[13],"considerable":[14],"time":[15,66],"and":[16,116,136,159,199],"energy":[17],"consumed":[18],"spectrum":[20,24,44,75,86,114,139],"sensing":[21],"process.":[22],"Many":[23],"algorithms":[26],"have":[27,61],"achieved":[28],"good":[29],"performance,":[30],"but":[31],"majority":[32],"of":[33,43,64,109,121,134,154,168,184,211],"them":[34],"with":[35,78,131,178,216,224],"shallow":[36],"architecture":[37],"cannot":[38],"capture":[39],"the":[40,89,100,105,119,142,151,155,174,182,186,195,209,212],"inherent":[41],"correlations":[42],"data":[45],"very":[46],"well.":[47,204],"Long":[48],"short-term":[49],"memory":[50],"(LSTM)":[51],"neural":[52,110,129,157,164,188,197,214],"network":[53,111,158,189,198,215],"deep":[55,80],"learning":[56,81],"has":[57,190],"been":[58],"validated":[59],"to":[60,92,103,145],"strong":[62],"capability":[63],"solving":[65],"series":[67],"problems.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72,97,126,149,206],"develop":[73],"framework":[77],"approach":[82],"on":[83],"two":[84,132],"real-world":[85],"datasets.":[87],"For":[88,141,166],"first":[90,229],"dataset":[91,144],"predict":[93,146],"channel":[94,147],"occupancy":[95],"states,":[96],"firstly":[98],"employ":[99],"taguchi":[101],"method":[102],"determine":[104],"best":[106],"optimized":[107],"configuration":[108],"for":[112,138],"certain":[113],"point":[115,183],"then":[117],"analyze":[118],"effect":[120],"each":[122],"design":[123],"hyper-parameter.":[124],"Next,":[125],"build":[127],"LSTM":[128,156,187,213],"networks":[130],"perspectives":[133],"regression":[135,225],"classification":[137,217],"prediction.":[140],"second":[143],"quality,":[148],"compare":[150],"performance":[153,176,193,210],"conventional":[160],"multilayer":[161],"perceptron":[162],"(MLP)":[163],"network.":[165],"both":[167],"our":[169,228],"datasets,":[170],"results":[171],"show":[172],"that":[173,208,223],"varies":[177],"frequency":[179],"bands.":[180],"From":[181],"statistics,":[185],"better":[191,221],"than":[194,222],"MLP":[196],"more":[201],"stable":[202],"as":[203],"Furthermore,":[205],"find":[207],"perspective":[218,226],"slightly":[220],"dataset.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}