{"id":"https://openalex.org/W7160899403","doi":"https://doi.org/10.1109/tkde.2026.3692700","title":"Knowledge Aware State-Space Capsule Network for Multivariate Time Series Classification","display_name":"Knowledge Aware State-Space Capsule Network for Multivariate Time Series Classification","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7160899403","doi":"https://doi.org/10.1109/tkde.2026.3692700"},"language":null,"primary_location":{"id":"doi:10.1109/tkde.2026.3692700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2026.3692700","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5050203956","display_name":"Zhiwen Xiao","orcid":"https://orcid.org/0000-0001-9651-111X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Xiao","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-9651-111X","affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101647266","display_name":"Qian Wan","orcid":"https://orcid.org/0000-0003-2320-1895"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Wan","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-2320-1895","affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135920608","display_name":"Weiping Ding","orcid":"https://orcid.org/0000-0002-3180-7347"},"institutions":[{"id":"https://openalex.org/I199305430","display_name":"Nantong University","ror":"https://ror.org/02afcvw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I199305430"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiping Ding","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Nantong University, Nantong, China"],"raw_orcid":"https://orcid.org/0000-0002-3180-7347","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Nantong University, Nantong, China","institution_ids":["https://openalex.org/I199305430"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062811522","display_name":"Fuhong Song","orcid":"https://orcid.org/0009-0005-0925-8133"},"institutions":[{"id":"https://openalex.org/I170172562","display_name":"Guizhou University of Finance and Economics","ror":"https://ror.org/02sw6yz40","country_code":"CN","type":"education","lineage":["https://openalex.org/I170172562"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuhong Song","raw_affiliation_strings":["Guizhou Provincial Key Laboratory of Computing and Network Convergence and School of Information, Guizhou University of Finance and Economics, Guiyang, China"],"raw_orcid":"https://orcid.org/0009-0005-0925-8133","affiliations":[{"raw_affiliation_string":"Guizhou Provincial Key Laboratory of Computing and Network Convergence and School of Information, Guizhou University of Finance and Economics, Guiyang, China","institution_ids":["https://openalex.org/I170172562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086563860","display_name":"Huagang Tong","orcid":"https://orcid.org/0000-0002-6076-9669"},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huagang Tong","raw_affiliation_strings":["College of Economic and Management, Nanjing Tech University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-6076-9669","affiliations":[{"raw_affiliation_string":"College of Economic and Management, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.9797,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.98603426,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"38","issue":"8","first_page":"5215","last_page":"5231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9588000178337097,"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":0.9588000178337097,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.00430000014603138,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.002300000051036477,"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/time-series","display_name":"Time series","score":0.5616999864578247},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4968000054359436},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.45559999346733093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44690001010894775},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3714999854564667},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3617999851703644},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3327000141143799}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8136000037193298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6243000030517578},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5616999864578247},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4968000054359436},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46239998936653137},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.45559999346733093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44690001010894775},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3714999854564667},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31679999828338623},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C3020028006","wikidata":"https://www.wikidata.org/wiki/Q9158","display_name":"Electronic mail","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2026.3692700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2026.3692700","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1591510878","display_name":null,"funder_award_id":"62006128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4286351655","display_name":null,"funder_award_id":"U2433216","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multivariate":[0],"time":[1],"series":[2],"classification":[3],"(MTSC)":[4],"requires":[5],"a":[6,76,88,126,142,283],"model":[7,40],"capable":[8],"of":[9,170],"capturing":[10,56],"both":[11,255,290],"localized":[12],"temporal":[13,94,158],"patterns":[14],"and":[15,64,122,129,160,207,226,251,260,285],"long-range":[16,41,136],"dependencies":[17],"while":[18,43,139],"effectively":[19],"modeling":[20],"complex":[21],"inter-variable":[22,208],"relationships.":[23],"Existing":[24],"convolutional":[25],"neural":[26],"network":[27],"(CNN)-based":[28],"capsule":[29,45,221],"models":[30,46],"suffer":[31],"from":[32],"limited":[33],"receptive":[34],"fields,":[35],"constraining":[36],"their":[37],"ability":[38],"to":[39,91,152,184,203],"dependencies,":[42],"transformer-based":[44,98],"rely":[47],"solely":[48],"on":[49,103],"self-attention,":[50,118],"which,":[51],"despite":[52],"its":[53],"effectiveness":[54],"in":[55,113,267],"global":[57,106],"features,":[58,194],"struggles":[59],"with":[60,87,269],"preserving":[61],"local":[62],"structures":[63],"efficiently":[65],"processing":[66,150],"long":[67],"sequences.":[68],"To":[69],"overcome":[70],"these":[71],"limitations,":[72],"we":[73],"propose":[74],"KACapMamba,":[75],"Knowledge-Aware":[77],"State-Space":[78],"Capsule":[79],"Network,":[80],"which":[81,180],"integrates":[82],"three":[83],"attentive":[84,110],"Mamba":[85,111,252],"blocks":[86],"routing":[89,212],"layer":[90,213],"achieve":[92],"hierarchical":[93,216],"modeling.":[95,209],"Unlike":[96],"conventional":[97],"methods":[99],"that":[100,237],"primarily":[101],"depend":[102],"self-attention":[104],"for":[105,148],"dependency":[107,137],"modeling,":[108,138],"each":[109],"block":[112],"KACapMamba":[114,238],"fuses":[115],"1-dimensional":[116],"CNNs,":[117],"state-space":[119],"module":[120],"(SSM),":[121],"mutual":[123,165,195],"cross-attention,":[124],"enabling":[125],"more":[127,198],"structured":[128],"adaptive":[130],"feature":[131,205,217,227],"representation.":[132],"Self-attention":[133],"ensures":[134],"effective":[135],"SSM":[140],"provides":[141],"recurrent-state":[143],"mechanism,":[144],"inherently":[145],"better":[146],"suited":[147],"sequential":[149],"compared":[151],"purely":[153],"attention-based":[154],"architectures,":[155],"thereby":[156],"enhancing":[157],"continuity":[159],"long-term":[161],"pattern":[162],"retention.":[163],"Notably,":[164],"cross-attention":[166,196],"addresses":[167],"the":[168,182,211,232,241,277],"limitations":[169],"traditional":[171],"fusion":[172],"strategies":[173],"such":[174],"as":[175],"element-wise":[176],"addition":[177],"or":[178],"multiplication,":[179],"lack":[181],"capacity":[183],"selectively":[185],"enhance":[186],"relevant":[187],"features.":[188],"By":[189],"dynamically":[190],"reweighting":[191],"interactions":[192],"between":[193],"enables":[197],"expressive,":[199],"context-aware":[200],"representations,":[201],"leading":[202,249],"improved":[204],"disentanglement":[206,218],"Additionally,":[210],"further":[214],"enhances":[215],"by":[219],"refining":[220],"activations,":[222],"reinforcing":[223],"structural":[224],"coherence":[225],"selectivity.":[228],"Experiments":[229],"conducted":[230],"across":[231,289],"UEA":[233],"benchmark":[234],"archive":[235],"demonstrate":[236],"consistently":[239],"achieves":[240],"highest":[242],"\u2018win\u2019/\u2018tie\u2019/\u2018lose\u2019/\u2018best\u2019":[243],"ratios":[244],"when":[245],"evaluated":[246],"against":[247],"10":[248],"transformer":[250],"architectures":[253],"under":[254],"<inline-formula":[256,261],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[257,262],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[258,263],"notation=\"LaTeX\">$Accuracy$</tex-math></inline-formula>":[259],"notation=\"LaTeX\">$F_{1}$</tex-math></inline-formula>":[264],"metrics.":[265],"Moreover,":[266],"comparison":[268],"22":[270],"state-of-the-art":[271],"MTSC":[272],"models,":[273],"it":[274],"again":[275],"secures":[276],"most":[278],"favorable":[279],"performance":[280],"profile,":[281],"demonstrating":[282],"clear":[284],"statistically":[286],"supported":[287],"advantage":[288],"evaluation":[291],"measures.":[292]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-10T05:49:55.623906","created_date":"2026-05-13T00:00:00"}
