{"id":"https://openalex.org/W3162915151","doi":"https://doi.org/10.1109/tits.2021.3076607","title":"User Behavior Analysis Based on Stacked Autoencoder and Clustering in Complex Power Grid Environment","display_name":"User Behavior Analysis Based on Stacked Autoencoder and Clustering in Complex Power Grid Environment","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3162915151","doi":"https://doi.org/10.1109/tits.2021.3076607","mag":"3162915151"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3076607","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3076607","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Intelligent Transportation Systems","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/A5001770391","display_name":"Song Deng","orcid":"https://orcid.org/0000-0002-8976-6592"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Song Deng","raw_affiliation_strings":["Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101476206","display_name":"Qingyuan Cai","orcid":"https://orcid.org/0000-0002-4600-4643"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyuan Cai","raw_affiliation_strings":["College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114254489","display_name":"Zi Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zi Zhang","raw_affiliation_strings":["School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080738591","display_name":"Xindong Wu","orcid":"https://orcid.org/0000-0003-2396-1704"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]},{"id":"https://openalex.org/I4401726980","display_name":"Mininglamp (China)","ror":"https://ror.org/04tb90x61","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401726980"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xindong Wu","raw_affiliation_strings":["Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education, Hefei University of Technology, Hefei, China","Mininglamp Academy of Sciences, Mininglamp Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]},{"raw_affiliation_string":"Mininglamp Academy of Sciences, Mininglamp Technology, Shanghai, China","institution_ids":["https://openalex.org/I4401726980"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5001770391"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":3.4092,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.92973423,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"23","issue":"12","first_page":"25521","last_page":"25535"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12451","display_name":"Smart Grid and Power Systems","score":0.9936000108718872,"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"}},"topics":[{"id":"https://openalex.org/T12451","display_name":"Smart Grid and Power Systems","score":0.9936000108718872,"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":0.9876000285148621,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9742000102996826,"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/autoencoder","display_name":"Autoencoder","score":0.8004576563835144},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7818528413772583},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7316604256629944},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6271498799324036},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.605492889881134},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5715389251708984},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5179897546768188},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5002334117889404},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.45705223083496094},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.1928269863128662}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8004576563835144},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7818528413772583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7316604256629944},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6271498799324036},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.605492889881134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5715389251708984},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5179897546768188},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5002334117889404},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.45705223083496094},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.1928269863128662},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2021.3076607","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3076607","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.41999998688697815,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G1280326437","display_name":null,"funder_award_id":"51977113","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1450990713","display_name":null,"funder_award_id":"91746209","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G443199372","display_name":null,"funder_award_id":"BK20190089","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G6255078559","display_name":null,"funder_award_id":"NY219095","funder_id":"https://openalex.org/F4320323268","funder_display_name":"Nanjing University of Posts and Telecommunications"},{"id":"https://openalex.org/G8465891786","display_name":null,"funder_award_id":"201979","funder_id":"https://openalex.org/F4320329877","funder_display_name":"Bagui Scholars Program of Guangxi Zhuang Autonomous Region"},{"id":"https://openalex.org/G939443868","display_name":null,"funder_award_id":"61972212","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/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323268","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34"},{"id":"https://openalex.org/F4320329877","display_name":"Bagui Scholars Program of Guangxi Zhuang Autonomous Region","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1990368529","https://openalex.org/W2059471177","https://openalex.org/W2059515884","https://openalex.org/W2079697937","https://openalex.org/W2087932775","https://openalex.org/W2089497633","https://openalex.org/W2128728535","https://openalex.org/W2142838865","https://openalex.org/W2209508536","https://openalex.org/W2328146686","https://openalex.org/W2363549572","https://openalex.org/W2513590440","https://openalex.org/W2562809553","https://openalex.org/W2604466268","https://openalex.org/W2744316982","https://openalex.org/W2767020045","https://openalex.org/W2788805965","https://openalex.org/W2790174894","https://openalex.org/W2810110363","https://openalex.org/W2905950019","https://openalex.org/W2906188288","https://openalex.org/W2911869788","https://openalex.org/W2940730057","https://openalex.org/W2944339461","https://openalex.org/W2945932910","https://openalex.org/W2963891069","https://openalex.org/W2963947916","https://openalex.org/W2969293360","https://openalex.org/W2982690457","https://openalex.org/W2998320282","https://openalex.org/W3004223592","https://openalex.org/W3006658573","https://openalex.org/W3014847672","https://openalex.org/W3015280312","https://openalex.org/W3026534984","https://openalex.org/W3037516875","https://openalex.org/W3038685580","https://openalex.org/W3044905940","https://openalex.org/W3045904793","https://openalex.org/W3046632728","https://openalex.org/W3065619135","https://openalex.org/W3083630455","https://openalex.org/W3089994530","https://openalex.org/W3092642546","https://openalex.org/W3101361680","https://openalex.org/W3187318797","https://openalex.org/W3208320926","https://openalex.org/W4250042253","https://openalex.org/W6731218148","https://openalex.org/W6774047709","https://openalex.org/W6777709984","https://openalex.org/W6780398477","https://openalex.org/W6782555207","https://openalex.org/W6785465503","https://openalex.org/W6798961829","https://openalex.org/W7004872083"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2806873178","https://openalex.org/W2965146396","https://openalex.org/W2770818364","https://openalex.org/W4312416532"],"abstract_inverted_index":{"Analyzing":[0],"user":[1,13,21,51,67,76,92,102,116,138],"behavior":[2,14,22,52,68,77,93,103,117,139],"characteristics":[3],"in":[4,53,69,182],"a":[5,115],"complex":[6,54,70],"power":[7,71],"grid":[8,55,72],"environment":[9],"is":[10],"essential":[11],"for":[12],"planning":[15],"and":[16,28,37,48,74,84,108,125,160,176,190],"resource":[17],"coordination":[18],"optimization.":[19],"Traditional":[20],"analysis":[23,30,78,118],"methods":[24,64,79],"based":[25,80,104,120],"on":[26,81,105,121,155],"model-driven":[27],"causal":[29],"have":[31,185],"the":[32,46,89,132,142,147,171,179],"disadvantages":[33],"of":[34,50,91,101,134,137,146],"strong":[35],"subjectivity":[36],"physical":[38],"models":[39],"that":[40,168],"are":[41],"difficult":[42],"to":[43,65],"deal":[44],"with":[45,170],"randomness":[47],"uncertainty":[49],"environments.":[56],"In":[57],"this":[58,183],"paper,":[59],"we":[60,113],"use":[61],"unsupervised":[62,109,135],"learning":[63,110],"analyze":[66],"environments,":[73],"propose":[75],"stacked":[82,106],"autoencoder":[83,107],"clustering.":[85],"We":[86],"first":[87],"reduce":[88],"complexity":[90],"data":[94],"by":[95,140],"proposing":[96],"adaptive":[97,122,143],"feature":[98,123,173,187],"selection":[99,124,174,188],"algorithm":[100,175],"(AFS-SAEUL).":[111],"Finally,":[112],"build":[114],"model":[119,130],"improved":[126,131],"clustering":[127,177,192],"(UBA-AFSIC).":[128],"The":[129,151],"performance":[133],"classification":[136],"fusing":[141],"generation":[144],"strategy":[145],"initial":[148],"cluster":[149],"centers.":[150],"simulation":[152],"experiment":[153],"results":[154],"two":[156],"real":[157],"electricity":[158],"datasets":[159],"one":[161],"public":[162],"electric":[163],"vehicle":[164],"charging":[165],"dataset":[166],"show":[167],"compared":[169],"existing":[172],"algorithm,":[178],"algorithms":[180],"proposed":[181],"paper":[184],"higher":[186],"rate":[189],"better":[191],"performance.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
