{"id":"https://openalex.org/W3112406413","doi":"https://doi.org/10.3390/e22121414","title":"Whole Time Series Data Streams Clustering: Dynamic Profiling of the Electricity Consumption","display_name":"Whole Time Series Data Streams Clustering: Dynamic Profiling of the Electricity Consumption","publication_year":2020,"publication_date":"2020-12-15","ids":{"openalex":"https://openalex.org/W3112406413","doi":"https://doi.org/10.3390/e22121414","mag":"3112406413","pmid":"https://pubmed.ncbi.nlm.nih.gov/33333937"},"language":"en","primary_location":{"id":"doi:10.3390/e22121414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22121414","pdf_url":"https://www.mdpi.com/1099-4300/22/12/1414/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/22/12/1414/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047203445","display_name":"Krzysztof Gajowniczek","orcid":"https://orcid.org/0000-0001-6953-8907"},"institutions":[{"id":"https://openalex.org/I170230895","display_name":"Warsaw University of Life Sciences","ror":"https://ror.org/05srvzs48","country_code":"PL","type":"education","lineage":["https://openalex.org/I170230895"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Krzysztof Gajowniczek","raw_affiliation_strings":["Department of Artificial Intelligence, Institute of Information Technology, Warsaw University of Life Sciences-SGGW, 02-776 Warsaw, Poland"],"raw_orcid":"https://orcid.org/0000-0001-6953-8907","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Institute of Information Technology, Warsaw University of Life Sciences-SGGW, 02-776 Warsaw, Poland","institution_ids":["https://openalex.org/I170230895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020572194","display_name":"Marcin Bator","orcid":"https://orcid.org/0000-0002-6881-3695"},"institutions":[{"id":"https://openalex.org/I170230895","display_name":"Warsaw University of Life Sciences","ror":"https://ror.org/05srvzs48","country_code":"PL","type":"education","lineage":["https://openalex.org/I170230895"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Marcin Bator","raw_affiliation_strings":["Department of Artificial Intelligence, Institute of Information Technology, Warsaw University of Life Sciences-SGGW, 02-776 Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Institute of Information Technology, Warsaw University of Life Sciences-SGGW, 02-776 Warsaw, Poland","institution_ids":["https://openalex.org/I170230895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029575854","display_name":"Tomasz Z\u0105bkowski","orcid":"https://orcid.org/0000-0003-1722-1179"},"institutions":[{"id":"https://openalex.org/I170230895","display_name":"Warsaw University of Life Sciences","ror":"https://ror.org/05srvzs48","country_code":"PL","type":"education","lineage":["https://openalex.org/I170230895"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Tomasz Z\u0105bkowski","raw_affiliation_strings":["Department of Artificial Intelligence, Institute of Information Technology, Warsaw University of Life Sciences-SGGW, 02-776 Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Institute of Information Technology, Warsaw University of Life Sciences-SGGW, 02-776 Warsaw, Poland","institution_ids":["https://openalex.org/I170230895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047203445"],"corresponding_institution_ids":["https://openalex.org/I170230895"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.6242,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.69101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"22","issue":"12","first_page":"1414","last_page":"1414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9997000098228455,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9997000098228455,"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":0.9991000294685364,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.998199999332428,"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":0.7826559543609619},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7769421339035034},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7026432156562805},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6432607769966125},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.5779434442520142},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5622267127037048},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.5412532687187195},{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.5315290093421936},{"id":"https://openalex.org/keywords/skewness","display_name":"Skewness","score":0.5005960464477539},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4387490153312683},{"id":"https://openalex.org/keywords/transaction-data","display_name":"Transaction data","score":0.4355659782886505},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.431826114654541},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.268210232257843},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.21451881527900696},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.19430240988731384},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15155336260795593},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15038010478019714},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.1494481861591339}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7826559543609619},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7769421339035034},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7026432156562805},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6432607769966125},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.5779434442520142},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5622267127037048},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.5412532687187195},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.5315290093421936},{"id":"https://openalex.org/C122342681","wikidata":"https://www.wikidata.org/wiki/Q330828","display_name":"Skewness","level":2,"score":0.5005960464477539},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4387490153312683},{"id":"https://openalex.org/C127722929","wikidata":"https://www.wikidata.org/wiki/Q7833714","display_name":"Transaction data","level":3,"score":0.4355659782886505},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.431826114654541},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.268210232257843},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.21451881527900696},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.19430240988731384},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15155336260795593},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15038010478019714},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.1494481861591339},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e22121414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22121414","pdf_url":"https://www.mdpi.com/1099-4300/22/12/1414/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:33333937","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33333937","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:95394ae0f5084726be915753b0ab6659","is_oa":true,"landing_page_url":"https://doaj.org/article/95394ae0f5084726be915753b0ab6659","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":"Entropy, Vol 22, Iss 12, p 1414 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/22/12/1414/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e22121414","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 22; Issue 12; Pages: 1414","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7765420","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7765420","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e22121414","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22121414","pdf_url":"https://www.mdpi.com/1099-4300/22/12/1414/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3112406413.pdf","grobid_xml":"https://content.openalex.org/works/W3112406413.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1016015581","https://openalex.org/W1517466436","https://openalex.org/W1519566594","https://openalex.org/W1540607020","https://openalex.org/W1598395355","https://openalex.org/W1826290430","https://openalex.org/W1852309679","https://openalex.org/W1987799824","https://openalex.org/W1992419399","https://openalex.org/W1994211684","https://openalex.org/W1994710124","https://openalex.org/W2001376071","https://openalex.org/W2004787755","https://openalex.org/W2010214994","https://openalex.org/W2023784161","https://openalex.org/W2043568875","https://openalex.org/W2048442462","https://openalex.org/W2051224630","https://openalex.org/W2058437258","https://openalex.org/W2070198522","https://openalex.org/W2071151783","https://openalex.org/W2075485829","https://openalex.org/W2079697937","https://openalex.org/W2088340225","https://openalex.org/W2092335550","https://openalex.org/W2103016999","https://openalex.org/W2103226621","https://openalex.org/W2103430225","https://openalex.org/W2110366306","https://openalex.org/W2117604780","https://openalex.org/W2128462276","https://openalex.org/W2160863575","https://openalex.org/W2170936641","https://openalex.org/W2272544077","https://openalex.org/W2272985318","https://openalex.org/W2343620495","https://openalex.org/W2743219614","https://openalex.org/W2755239606","https://openalex.org/W2773997834","https://openalex.org/W2789696622","https://openalex.org/W2799404019","https://openalex.org/W2803606270","https://openalex.org/W2891681985","https://openalex.org/W2901144298","https://openalex.org/W2940445895","https://openalex.org/W2979558831","https://openalex.org/W2999729612","https://openalex.org/W3008846063","https://openalex.org/W3101117497","https://openalex.org/W4230080154","https://openalex.org/W4231029117","https://openalex.org/W6653071931"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W2360131081","https://openalex.org/W2522231769","https://openalex.org/W4312214159","https://openalex.org/W2045938006","https://openalex.org/W2079625735"],"abstract_inverted_index":{"Data":[0],"from":[1,156],"smart":[2,179],"grids":[3],"are":[4,82,120],"challenging":[5],"to":[6,9,41,70,136,149,170],"analyze":[7],"due":[8],"their":[10,52,165],"very":[11],"large":[12,79],"size,":[13],"high":[14],"dimensionality,":[15],"skewness,":[16],"sparsity,":[17],"and":[18,25,61,88,143],"number":[19],"of":[20,57,101,110,118,140],"seasonal":[21],"fluctuations,":[22],"including":[23],"daily":[24],"weekly":[26],"effects.":[27],"With":[28],"the":[29,36,44,58,72,78,86,89,99,108,124,129,145,150,172],"data":[30,49,59,62,74,80,113,126],"arriving":[31],"in":[32,55,75,174],"a":[33,111,116],"sequential":[34],"form":[35],"underlying":[37],"distribution":[38],"is":[39,67],"subject":[40],"changes":[42],"over":[43],"time":[45],"intervals.":[46],"Time":[47],"series":[48],"streams":[50,127],"have":[51],"own":[53],"specifics":[54],"terms":[56],"processing":[60,87],"analysis":[63,90],"because,":[64],"usually,":[65],"it":[66],"not":[68],"possible":[69],"process":[71],"whole":[73,125],"memory":[76],"as":[77],"volumes":[81],"generated":[83],"fast":[84],"so":[85,152],"should":[91],"be":[92],"done":[93],"incrementally":[94],"using":[95],"sliding":[96],"windows.":[97],"Despite":[98],"proposal":[100],"many":[102],"clustering":[103],"techniques":[104],"applicable":[105],"for":[106],"grouping":[107],"observations":[109],"single":[112],"stream,":[114],"only":[115],"few":[117],"them":[119],"focused":[121],"on":[122,178],"splitting":[123],"into":[128],"clusters.":[130],"In":[131],"this":[132],"article":[133],"we":[134],"aim":[135],"explore":[137],"individual":[138],"characteristics":[139],"electricity":[141],"usage":[142],"recommend":[144],"most":[146],"suitable":[147],"tariff":[148],"customer":[151],"they":[153],"can":[154],"benefit":[155],"lower":[157],"prices.":[158],"This":[159],"work":[160],"investigates":[161],"various":[162],"algorithms":[163],"(and":[164],"improvements)":[166],"what":[167],"allows":[168],"us":[169],"formulate":[171],"clusters,":[173],"real":[175],"time,":[176],"based":[177],"meter":[180],"data.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}