{"id":"https://openalex.org/W3031974964","doi":"https://doi.org/10.1145/3383972.3384013","title":"Multivariate Time Series Classification Based on MCNN-LSTMs Network","display_name":"Multivariate Time Series Classification Based on MCNN-LSTMs Network","publication_year":2020,"publication_date":"2020-02-15","ids":{"openalex":"https://openalex.org/W3031974964","doi":"https://doi.org/10.1145/3383972.3384013","mag":"3031974964"},"language":"en","primary_location":{"id":"doi:10.1145/3383972.3384013","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383972.3384013","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 12th International Conference on Machine Learning and Computing","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/A5007911614","display_name":"Zhiqiang Guo","orcid":"https://orcid.org/0000-0001-9393-4854"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhiqiang Guo","raw_affiliation_strings":["Hubei Provincial Key Laboratory of Broadband Wireless Communication and Sensor Networks, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"Hubei Provincial Key Laboratory of Broadband Wireless Communication and Sensor Networks, Wuhan, Hubei, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346828","display_name":"Peng Liu","orcid":"https://orcid.org/0000-0002-5091-8464"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Liu","raw_affiliation_strings":["School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101445040","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0003-1317-8142"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080783188","display_name":"Yongwu Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongwu Hu","raw_affiliation_strings":["School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007911614"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9129,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.737816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"510","last_page":"517"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9991000294685364,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9991000294685364,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9595999717712402,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.953499972820282,"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":0.7551950812339783},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7482549548149109},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6442605257034302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6276329755783081},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5060984492301941},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.503682553768158},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4938676953315735},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.46088194847106934},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4546296298503876},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45303285121917725},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44219398498535156},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42529192566871643},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3947839140892029},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24489769339561462}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7551950812339783},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7482549548149109},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6442605257034302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6276329755783081},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5060984492301941},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.503682553768158},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4938676953315735},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.46088194847106934},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4546296298503876},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45303285121917725},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44219398498535156},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42529192566871643},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3947839140892029},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24489769339561462},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3383972.3384013","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383972.3384013","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 12th International Conference on Machine Learning and Computing","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":9,"referenced_works":["https://openalex.org/W119403003","https://openalex.org/W140867740","https://openalex.org/W1832693441","https://openalex.org/W1951216520","https://openalex.org/W2097117768","https://openalex.org/W2160535745","https://openalex.org/W2163605009","https://openalex.org/W2187089797","https://openalex.org/W2949117887"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2406638334","https://openalex.org/W4390961098","https://openalex.org/W1991765889","https://openalex.org/W1990068454","https://openalex.org/W2472172556","https://openalex.org/W4321487865","https://openalex.org/W1570805059","https://openalex.org/W2357266745","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Multivariate":[0],"time":[1,17,47,62,81,169],"series":[2,18,63,170],"data":[3,150],"has":[4,160],"high":[5],"latitude,":[6],"variable":[7],"length,":[8],"coupling,":[9],"multi-scale":[10,55,67,94,101],"and":[11,37,69,116,120,146],"other":[12],"characteristics.":[13],"The":[14,142,152],"existing":[15,166],"multivariate":[16,46,61],"classification":[19,162,171],"methods":[20],"often":[21],"extract":[22,92,112],"a":[23],"single":[24],"type":[25],"of":[26,45,75,88,123],"feature":[27,31],"through":[28],"complex":[29],"artificial":[30],"engineering":[32],"or":[33],"deep":[34],"neural":[35,56],"network,":[36],"do":[38],"not":[39],"fully":[40,137],"exploit":[41],"the":[42,73,99,107,118,124,130,136,157,165],"multi-class":[43],"features":[44,103,122,126,132],"series.":[48],"Therefore,":[49],"this":[50],"paper":[51],"proposes":[52],"an":[53],"end-to-end":[54],"network":[57,109,158],"model":[58,143,159],"MCNN-LSTMs":[59],"for":[60,140],"classification.":[64,141],"Firstly,":[65],"using":[66,84],"entropy":[68],"Inceptions":[70],"structure":[71],"ideas,":[72],"subsequences":[74],"each":[76],"channel":[77],"are":[78,104,127,133],"convolved":[79],"in":[80],"dimension":[82],"by":[83],"one-dimensional":[85],"convolution":[86],"kernels":[87],"different":[89],"sizes":[90],"to":[91,110],"high-level":[93],"spatial":[95,102,121],"abstract":[96],"features.":[97],"Secondly,":[98],"extracted":[100],"input":[105,134],"into":[106,135],"FC-LSTM":[108],"further":[111],"their":[113],"temporal":[114,119],"features,":[115],"then":[117],"captured":[125],"fused.":[128],"Finally,":[129],"fused":[131],"connected":[138],"layer":[139],"is":[144],"tested":[145],"evaluated":[147],"on":[148],"multiple":[149,167],"sets.":[151],"experimental":[153],"results":[154],"show":[155],"that":[156],"better":[161],"effect":[163],"than":[164],"representative":[168],"methods.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}