{"id":"https://openalex.org/W7225327272","doi":"https://doi.org/10.4108/ew.16579","title":"Deep Clustering and Adaptive Mode Decomposition of Industrial Loads for Temporal Complexity","display_name":"Deep Clustering and Adaptive Mode Decomposition of Industrial Loads for Temporal Complexity","publication_year":2026,"publication_date":"2026-11-05","ids":{"openalex":"https://openalex.org/W7225327272","doi":"https://doi.org/10.4108/ew.16579"},"language":"en","primary_location":{"id":"doi:10.4108/ew.16579","doi":"https://doi.org/10.4108/ew.16579","is_oa":true,"landing_page_url":"https://doi.org/10.4108/ew.16579","pdf_url":"https://publications.eai.eu/index.php/ew/article/download/16579/4527","source":{"id":"https://openalex.org/S2738613471","display_name":"EAI Endorsed Transactions on Energy Web","issn_l":"2032-944X","issn":["2032-944X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310321145","host_organization_name":"European Alliance for Innovation","host_organization_lineage":["https://openalex.org/P4310321145"],"host_organization_lineage_names":["European Alliance for Innovation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EAI Endorsed Transactions on Energy Web","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://publications.eai.eu/index.php/ew/article/download/16579/4527","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101411506","display_name":"Shun Yan","orcid":"https://orcid.org/0000-0003-2468-5799","observed_orcids":["https://orcid.org/0000-0003-2468-5799"]},"institutions":[{"id":"https://openalex.org/I4210120842","display_name":"Shenyang Institute of Computing Technology (China)","ror":"https://ror.org/02xqp7x96","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120842"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shun Yan","raw_affiliation_strings":["Shenyang Institute of Computing Technology (China)","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Institute of Computing Technology (China)","institution_ids":["https://openalex.org/I4210120842"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160959021","display_name":"Li Lv","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210120842","display_name":"Shenyang Institute of Computing Technology (China)","ror":"https://ror.org/02xqp7x96","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120842"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Lv","raw_affiliation_strings":["Shenyang Institute of Computing Technology (China)","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Institute of Computing Technology (China)","institution_ids":["https://openalex.org/I4210120842"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087883426","display_name":"Zengyao Tian","orcid":"https://orcid.org/0000-0001-5476-6851","observed_orcids":["https://orcid.org/0000-0001-5476-6851"]},"institutions":[{"id":"https://openalex.org/I4210120842","display_name":"Shenyang Institute of Computing Technology (China)","ror":"https://ror.org/02xqp7x96","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120842"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengyao Tian","raw_affiliation_strings":["Shenyang Institute of Computing Technology (China)","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Institute of Computing Technology (China)","institution_ids":["https://openalex.org/I4210120842"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160884219","display_name":"Qun Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210120842","display_name":"Shenyang Institute of Computing Technology (China)","ror":"https://ror.org/02xqp7x96","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120842"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qun Wang","raw_affiliation_strings":["Shenyang Institute of Computing Technology (China)","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Institute of Computing Technology (China)","institution_ids":["https://openalex.org/I4210120842"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130598820","display_name":"Yanqing Zhao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210120842","display_name":"Shenyang Institute of Computing Technology (China)","ror":"https://ror.org/02xqp7x96","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120842"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanqing Zhao","raw_affiliation_strings":["Shenyang Institute of Computing Technology (China)","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Institute of Computing Technology (China)","institution_ids":["https://openalex.org/I4210120842"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.33059999346733093,"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":0.33059999346733093,"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/T10603","display_name":"Smart Grid Energy Management","score":0.24650000035762787,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.19580000638961792,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-clustering","display_name":"deep clustering","score":0.7919999957084656},{"id":"https://openalex.org/keywords/ceemdan","display_name":"CEEMDAN","score":0.7179999947547913},{"id":"https://openalex.org/keywords/vmd","display_name":"VMD","score":0.7049999833106995},{"id":"https://openalex.org/keywords/northern-goshawk-optimization","display_name":"Northern Goshawk Optimization","score":0.8709999918937683},{"id":"https://openalex.org/keywords/time-frequency-features","display_name":"time-frequency features","score":0.5070000290870667}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6973999738693237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.642300009727478},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6401000022888184},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5120000243186951},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4887000024318695},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48190000653266907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47290000319480896},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.4018999934196472},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.391400009393692},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3837999999523163},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.3521000146865845},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.2930999994277954},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28850001096725464},{"id":"https://openalex.org/C2778258933","wikidata":"https://www.wikidata.org/wiki/Q16918986","display_name":"Decomposition method (queueing theory)","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C2776784348","wikidata":"https://www.wikidata.org/wiki/Q5762595","display_name":"Microgrid","level":3,"score":0.2606000006198883},{"id":"https://openalex.org/C2779478453","wikidata":"https://www.wikidata.org/wiki/Q6889748","display_name":"Modularity (biology)","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4108/ew.16579","doi":"https://doi.org/10.4108/ew.16579","is_oa":true,"landing_page_url":"https://doi.org/10.4108/ew.16579","pdf_url":"https://publications.eai.eu/index.php/ew/article/download/16579/4527","source":{"id":"https://openalex.org/S2738613471","display_name":"EAI Endorsed Transactions on Energy Web","issn_l":"2032-944X","issn":["2032-944X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310321145","host_organization_name":"European Alliance for Innovation","host_organization_lineage":["https://openalex.org/P4310321145"],"host_organization_lineage_names":["European Alliance for Innovation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EAI Endorsed Transactions on Energy Web","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.4108/ew.16579","doi":"https://doi.org/10.4108/ew.16579","is_oa":true,"landing_page_url":"https://doi.org/10.4108/ew.16579","pdf_url":"https://publications.eai.eu/index.php/ew/article/download/16579/4527","source":{"id":"https://openalex.org/S2738613471","display_name":"EAI Endorsed Transactions on Energy Web","issn_l":"2032-944X","issn":["2032-944X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310321145","host_organization_name":"European Alliance for Innovation","host_organization_lineage":["https://openalex.org/P4310321145"],"host_organization_lineage_names":["European Alliance for Innovation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EAI Endorsed Transactions on Energy Web","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.8970999717712402,"id":"https://metadata.un.org/sdg/9"},{"display_name":"Affordable and clean energy","score":0.75,"id":"https://metadata.un.org/sdg/7"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225327272.pdf","grobid_xml":"https://content.openalex.org/works/W7225327272.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4362641142","https://openalex.org/W4414267519","https://openalex.org/W3203130495","https://openalex.org/W4401864277","https://openalex.org/W4323308164","https://openalex.org/W7212168320","https://openalex.org/W4323026108","https://openalex.org/W2968303757","https://openalex.org/W4286213893","https://openalex.org/W4402861144"],"abstract_inverted_index":{"Accurate":[0],"extraction":[1,28,47,174],"of":[2,22,64,175,186,192,216],"underlying":[3],"features":[4,178],"from":[5,39],"electrical":[6],"loads":[7,73,197],"is":[8,33,57,70,103,127,134,146],"crucial":[9],"for":[10,72,213],"intelligent":[11],"microgrid":[12],"management.To":[13],"address":[14],"the":[15,53,61,130,162,166,169,182],"heterogeneous":[16],"characteristics":[17],"and":[18,67,76,100,141,151,165,179],"microscopic":[19],"nonstationary":[20],"properties":[21],"industrial":[23,222],"loads,":[24,83,116],"a":[25,44,84,117,209],"shunt-cooperative":[26],"feature":[27,46,202,211],"framework":[29],"relying":[30],"on":[31,125],"MSE":[32,56],"proposed":[34,170],"in":[35,190,221],"this":[36],"work.":[37],"Different":[38],"traditional":[40,187],"methods":[41,189],"that":[42],"use":[43],"single":[45],"or":[48],"clustering":[49,90,193],"model":[50,91],"to":[51,59,105,136,148],"process":[52],"entire":[54],"sequence,":[55],"introduced":[58,135],"quantify":[60],"dynamic":[62],"complexity":[63,131],"load":[65],"sequences,":[66],"effective":[68],"classification":[69],"performed":[71],"with":[74,92,97,161,204],"strong":[75,81],"weak":[77,114],"time-series":[78,82,115],"characteristics.":[79],"For":[80,113],"multi-view":[85],"Variational":[86],"AutoEncoder":[87],"(VAE)":[88],"deep":[89],"adaptive":[93],"dual-distance":[94],"metrics":[95],"fused":[96],"Euclidean":[98],"distance":[99,102],"LB_Keogh":[101],"constructed":[104],"accurately":[106],"extract":[107],"macroscopic":[108],"typical":[109],"power":[110,218],"consumption":[111,219],"patterns.":[112],"\u201ccoarse":[118],"screening-fine":[119],"classification\u201d":[120],"hybrid":[121],"decomposition":[122,188],"architecture":[123],"based":[124],"CEEMDAN-NGO-VMD":[126],"proposed,":[128],"where":[129],"index":[132],"(LZC)":[133],"adaptively":[137],"strip":[138],"low-frequency":[139],"trends":[140],"Northern":[142],"Goshawk":[143],"Optimization":[144],"(NGO)":[145],"used":[147],"optimize":[149],"VMD":[150],"suppress":[152],"high-frequency":[153],"mode":[154,183],"aliasing.":[155],"Simulation":[156],"results":[157],"show":[158],"that,":[159],"compared":[160],"CEEMDAN-only":[163],"method":[164,171],"NGO-VMD-only":[167],"algorithm,":[168],"achieves":[172],"accurate":[173],"multi-scale":[176],"time-frequency":[177],"effectively":[180],"overcomes":[181],"aliasing":[184],"problem":[185],"terms":[191],"performance.":[194],"Finally,":[195],"complex":[196],"are":[198],"reconstructed":[199],"into":[200],"multi-modal":[201,217],"components":[203],"clear":[205],"physical":[206],"meanings,":[207],"providing":[208],"reliable":[210],"basis":[212],"subsequent":[214],"identification":[215],"behaviors":[220],"microgrids.":[223]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-11-06T00:00:00"}