{"id":"https://openalex.org/W2102609947","doi":"https://doi.org/10.1109/ijcnn.2011.6033595","title":"Semi-supervised monitoring of electric load time series for unusual patterns","display_name":"Semi-supervised monitoring of electric load time series for unusual patterns","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2102609947","doi":"https://doi.org/10.1109/ijcnn.2011.6033595","mag":"2102609947"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2011.6033595","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2011.6033595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2011 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},"type":"conference-paper","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/A5064340262","display_name":"Nikolaos Kourentzes","orcid":"https://orcid.org/0000-0003-0211-5218"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nikolaos Kourentzes","raw_affiliation_strings":["Department of Management Science, Lancaster University Management School, Lancaster, UK","Department of Management Science at Lancaster University Management School, LA1 4YX, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Management Science, Lancaster University Management School, Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Department of Management Science at Lancaster University Management School, LA1 4YX, United Kingdom","institution_ids":["https://openalex.org/I67415387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044304248","display_name":"Sven F. Crone","orcid":"https://orcid.org/0000-0003-4952-318X"},"institutions":[{"id":"https://openalex.org/I67415387","display_name":"Lancaster University","ror":"https://ror.org/04f2nsd36","country_code":"GB","type":"education","lineage":["https://openalex.org/I67415387"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sven F. Crone","raw_affiliation_strings":["Department of Management Science, Lancaster University Management School, Lancaster, UK","Department of Management Science at Lancaster University Management School, LA1 4YX, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Management Science, Lancaster University Management School, Lancaster, UK","institution_ids":["https://openalex.org/I67415387"]},{"raw_affiliation_string":"Department of Management Science at Lancaster University Management School, LA1 4YX, United Kingdom","institution_ids":["https://openalex.org/I67415387"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I67415387"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.17615783,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"9","issue":null,"first_page":"2852","last_page":"2859"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9995999932289124,"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":0.9995999932289124,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9958000183105469,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9936000108718872,"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":0.7762113809585571},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6966546773910522},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6231231689453125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5832118988037109},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5658130645751953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5197075009346008},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5013883113861084},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.498382568359375},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.485371470451355},{"id":"https://openalex.org/keywords/electrical-load","display_name":"Electrical load","score":0.43463587760925293},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1074722409248352}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7762113809585571},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6966546773910522},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6231231689453125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5832118988037109},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5658130645751953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5197075009346008},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5013883113861084},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.498382568359375},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.485371470451355},{"id":"https://openalex.org/C77715397","wikidata":"https://www.wikidata.org/wiki/Q931447","display_name":"Electrical load","level":3,"score":0.43463587760925293},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1074722409248352},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2011.6033595","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2011.6033595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2011 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.lancs.ac.uk:56115","is_oa":false,"landing_page_url":"https://eprints.lancs.ac.uk/id/eprint/56115/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401916","display_name":"Lancaster EPrints (Lancaster University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67415387","host_organization_name":"Lancaster University","host_organization_lineage":["https://openalex.org/I67415387"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Contribution in Book/Report/Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1514907448","https://openalex.org/W1825077972","https://openalex.org/W1912982817","https://openalex.org/W1967412064","https://openalex.org/W1987169011","https://openalex.org/W2001165499","https://openalex.org/W2016210396","https://openalex.org/W2024760831","https://openalex.org/W2042506099","https://openalex.org/W2056043406","https://openalex.org/W2079057609","https://openalex.org/W2101210369","https://openalex.org/W2113271473","https://openalex.org/W2122966123","https://openalex.org/W2126455177","https://openalex.org/W2129281431","https://openalex.org/W2131534673","https://openalex.org/W2133218851","https://openalex.org/W2137130182","https://openalex.org/W2145732764","https://openalex.org/W2153675946","https://openalex.org/W2286201810","https://openalex.org/W2313953460","https://openalex.org/W2325696188","https://openalex.org/W2798058877","https://openalex.org/W3121960989","https://openalex.org/W3125299673","https://openalex.org/W3143059483","https://openalex.org/W4250766106","https://openalex.org/W4253461361","https://openalex.org/W4290960458","https://openalex.org/W6651008772"],"related_works":["https://openalex.org/W2770593030","https://openalex.org/W3154990682","https://openalex.org/W1919101720","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"In":[0,21],"this":[1],"paper":[2],"we":[3],"propose":[4],"a":[5],"semi-supervised":[6],"neural":[7],"network":[8,74],"algorithm":[9],"to":[10,66],"identify":[11],"unusual":[12],"load":[13,123],"patterns":[14,44],"in":[15,38,45],"hourly":[16],"electricity":[17,122],"demand":[18],"time":[19],"series.":[20,47],"spite":[22],"of":[23,62,70],"several":[24],"modeling":[25],"and":[26,40,55,79,94,99,111,118],"forecasting":[27],"methodologies":[28],"that":[29],"have":[30,34],"been":[31,35],"proposed,":[32],"there":[33],"limited":[36],"advancements":[37],"monitoring":[39],"automatically":[41,83],"identifying":[42],"outlying":[43],"such":[46,63,101],"This":[48,89],"becomes":[49],"more":[50,85],"important":[51],"considering":[52],"the":[53,56,67,92,105],"difficulty":[54],"cost":[57,93],"associated":[58,96],"with":[59,97,108],"manual":[60],"exploration":[61],"data,":[64],"due":[65],"vast":[68],"number":[69],"observations.":[71],"The":[72],"proposed":[73,106],"learns":[75],"from":[76],"both":[77],"labeled":[78],"unlabeled":[80],"patterns,":[81],"adapting":[82],"as":[84],"data":[86],"become":[87],"available.":[88],"drastically":[90],"limits":[91],"effort":[95],"exploring":[98],"labeling":[100],"data.":[102,124],"We":[103],"compare":[104],"method":[107],"conventional":[109],"supervised":[110],"unsupervised":[112],"approaches,":[113],"demonstrating":[114],"higher":[115],"accuracy,":[116],"robustness":[117],"efficacy":[119],"on":[120],"empirical":[121]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
