{"id":"https://openalex.org/W4318147411","doi":"https://doi.org/10.1109/bigdata55660.2022.10020342","title":"Outlier Elimination Procedure for Power Curve Modeling of Wind Generation","display_name":"Outlier Elimination Procedure for Power Curve Modeling of Wind Generation","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4318147411","doi":"https://doi.org/10.1109/bigdata55660.2022.10020342"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020342","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-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/A5038574538","display_name":"Chun-Hyun Paik","orcid":"https://orcid.org/0000-0002-0354-8325"},"institutions":[{"id":"https://openalex.org/I204974687","display_name":"Dong-Eui University","ror":"https://ror.org/059g69b28","country_code":"KR","type":"education","lineage":["https://openalex.org/I204974687"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Chunhyun Paik","raw_affiliation_strings":["Dongeui University,Dept. of Industrial Convergence Systems Engineering,Busan,Rebublic of Korea","Dept. of Industrial Convergence Systems Engineering, Dongeui University, Busan, Rebublic of Korea"],"affiliations":[{"raw_affiliation_string":"Dongeui University,Dept. of Industrial Convergence Systems Engineering,Busan,Rebublic of Korea","institution_ids":["https://openalex.org/I204974687"]},{"raw_affiliation_string":"Dept. of Industrial Convergence Systems Engineering, Dongeui University, Busan, Rebublic of Korea","institution_ids":["https://openalex.org/I204974687"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070004655","display_name":"Yong-Joo Chung","orcid":"https://orcid.org/0000-0002-0060-1178"},"institutions":[{"id":"https://openalex.org/I83015752","display_name":"Busan University of Foreign Studies","ror":"https://ror.org/0455zdm83","country_code":"KR","type":"education","lineage":["https://openalex.org/I83015752"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongjoo Chung","raw_affiliation_strings":["Busan University of Foreign Studies,Dept. of e-Business,Busan,Republic of Korea","Dept. of e-Business, Busan University of Foreign Studies, Busan, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Busan University of Foreign Studies,Dept. of e-Business,Busan,Republic of Korea","institution_ids":["https://openalex.org/I83015752"]},{"raw_affiliation_string":"Dept. of e-Business, Busan University of Foreign Studies, Busan, Republic of Korea","institution_ids":["https://openalex.org/I83015752"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100387390","display_name":"Young Jin Kim","orcid":"https://orcid.org/0000-0003-3502-5112"},"institutions":[{"id":"https://openalex.org/I8991828","display_name":"Pukyong National University","ror":"https://ror.org/0433kqc49","country_code":"KR","type":"education","lineage":["https://openalex.org/I8991828"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Young Jin Kim","raw_affiliation_strings":["Innovation Research Institute Pukyong National University,Dept. of Systems Management and Engineering &#x0026; Industrial Systems,Busan,Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Innovation Research Institute Pukyong National University,Dept. of Systems Management and Engineering &#x0026; Industrial Systems,Busan,Republic of Korea","institution_ids":["https://openalex.org/I8991828"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038574538"],"corresponding_institution_ids":["https://openalex.org/I204974687"],"apc_list":null,"apc_paid":null,"fwci":0.3222,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50528901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"6705","last_page":"6707"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9987999796867371,"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":0.9987999796867371,"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/T10680","display_name":"Wind Energy Research and Development","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9909999966621399,"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/wind-power","display_name":"Wind power","score":0.7895241975784302},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7576864957809448},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.59207683801651},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5407076478004456},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5150927901268005},{"id":"https://openalex.org/keywords/curve-fitting","display_name":"Curve fitting","score":0.48661765456199646},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4819081127643585},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.45105305314064026},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.44017383456230164},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.28667742013931274},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2767941951751709},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2726367115974426},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23311766982078552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17466199398040771},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.11798989772796631},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11492183804512024},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07898983359336853},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.07141005992889404}],"concepts":[{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.7895241975784302},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7576864957809448},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.59207683801651},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5407076478004456},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5150927901268005},{"id":"https://openalex.org/C184389593","wikidata":"https://www.wikidata.org/wiki/Q603159","display_name":"Curve fitting","level":2,"score":0.48661765456199646},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4819081127643585},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.45105305314064026},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.44017383456230164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28667742013931274},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2767941951751709},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2726367115974426},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23311766982078552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17466199398040771},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.11798989772796631},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11492183804512024},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07898983359336853},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.07141005992889404},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata55660.2022.10020342","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1490477294","https://openalex.org/W1976383685","https://openalex.org/W2099506356","https://openalex.org/W2326041979","https://openalex.org/W2475727944","https://openalex.org/W2538056815","https://openalex.org/W2603332837","https://openalex.org/W2787400151","https://openalex.org/W2787528688","https://openalex.org/W2981208062","https://openalex.org/W3049512327","https://openalex.org/W6629136034"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W4380482219","https://openalex.org/W4377969695","https://openalex.org/W2028780417"],"abstract_inverted_index":{"The":[0],"estimation":[1,47],"of":[2,14,32,54,71,82,95],"power":[3,16,35,45,69,83,93],"curve":[4,46],"is":[5,19,89],"the":[6,21,25,44,49,86],"central":[7],"task":[8],"for":[9,62,67,91],"efficient":[10],"operation":[11],"and":[12,42,51,65],"prediction":[13],"wind":[15,40,72,97,102],"generation.":[17],"It":[18],"often":[20],"case,":[22],"however,":[23],"that":[24],"actual":[26],"data":[27],"exhibit":[28],"a":[29,59,100],"great":[30],"deal":[31],"variations":[33],"in":[34,99],"output":[36,84],"with":[37],"respect":[38],"to":[39],"speed,":[41],"thus":[43],"necessitates":[48],"detection":[50,64],"proper":[52],"treatment":[53],"outliers.":[55],"This":[56],"study":[57],"proposes":[58],"novel":[60],"procedure":[61],"outlier":[63],"elimination":[66],"estimating":[68],"curves":[70,94],"farms":[73],"by":[74],"employing":[75],"clustering":[76],"algorithms.":[77],"Employing":[78],"different":[79],"parametric":[80],"models":[81],"curve,":[85],"proposed":[87],"methodology":[88],"demonstrated":[90],"obtaining":[92],"individual":[96],"turbines":[98],"Korean":[101],"farm.":[103]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
