{"id":"https://openalex.org/W1974845639","doi":"https://doi.org/10.1155/2014/835791","title":"Support Vector Regression Based on Grid-Search Method for Short-Term Wind Power Forecasting","display_name":"Support Vector Regression Based on Grid-Search Method for Short-Term Wind Power Forecasting","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W1974845639","doi":"https://doi.org/10.1155/2014/835791","mag":"1974845639"},"language":"en","primary_location":{"id":"doi:10.1155/2014/835791","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2014/835791","pdf_url":"https://downloads.hindawi.com/journals/jam/2014/835791.pdf","source":{"id":"https://openalex.org/S190082376","display_name":"Journal of Applied Mathematics","issn_l":"1110-757X","issn":["1110-757X","1687-0042"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Applied Mathematics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/jam/2014/835791.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084113891","display_name":"Hong Zhang","orcid":"https://orcid.org/0000-0003-1276-0720"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Zhang","raw_affiliation_strings":["Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210096, China","School of Electrical Engineering, Southeast University, Nanjing, Jiangsu 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210096, China","institution_ids":[]},{"raw_affiliation_string":"School of Electrical Engineering, Southeast University, Nanjing, Jiangsu 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101982898","display_name":"Lixing Chen","orcid":"https://orcid.org/0000-0001-5015-0005"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixing Chen","raw_affiliation_strings":["Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210096, China","School of Electrical Engineering, Southeast University, Nanjing, Jiangsu 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210096, China","institution_ids":[]},{"raw_affiliation_string":"School of Electrical Engineering, Southeast University, Nanjing, Jiangsu 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041987715","display_name":"Yong Qu","orcid":"https://orcid.org/0000-0001-9244-8133"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yong Qu","raw_affiliation_strings":["VLSI Lab, Nanyang Technological University, Singapore 639798"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VLSI Lab, Nanyang Technological University, Singapore 639798","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090608616","display_name":"Guo Zhao","orcid":"https://orcid.org/0000-0002-9449-9724"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guo Zhao","raw_affiliation_strings":["Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210096, China","School of Electrical Engineering, Southeast University, Nanjing, Jiangsu 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Smart Grid Technology and Equipment, Nanjing 210096, China","institution_ids":[]},{"raw_affiliation_string":"School of Electrical Engineering, Southeast University, Nanjing, Jiangsu 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101540050","display_name":"Zhenwei Guo","orcid":"https://orcid.org/0000-0002-5773-1491"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenwei Guo","raw_affiliation_strings":["School of Information Science and Engineering, Hunan University, Changsha 410082, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Hunan University, Changsha 410082, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5084113891"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":1025,"currency":"USD","value_usd":1025},"apc_paid":{"value":1025,"currency":"USD","value_usd":1025},"fwci":0.6386,"has_fulltext":true,"cited_by_count":38,"citation_normalized_percentile":{"value":0.72359769,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2014","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9998000264167786,"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":0.9998000264167786,"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/T12368","display_name":"Grey System Theory Applications","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.6728911399841309},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6597923040390015},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.6040536165237427},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.6039621829986572},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6035407781600952},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5739843845367432},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5587893128395081},{"id":"https://openalex.org/keywords/wind-power-forecasting","display_name":"Wind power forecasting","score":0.5019016265869141},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.454412579536438},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.4371321201324463},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4220958352088928},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.42042529582977295},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.41482454538345337},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41028711199760437},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.3310365676879883},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.32831698656082153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3140140175819397},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17991000413894653}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6728911399841309},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6597923040390015},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.6040536165237427},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.6039621829986572},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6035407781600952},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5739843845367432},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5587893128395081},{"id":"https://openalex.org/C2781084341","wikidata":"https://www.wikidata.org/wiki/Q2583670","display_name":"Wind power forecasting","level":4,"score":0.5019016265869141},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.454412579536438},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.4371321201324463},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4220958352088928},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.42042529582977295},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.41482454538345337},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41028711199760437},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.3310365676879883},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.32831698656082153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3140140175819397},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17991000413894653},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1155/2014/835791","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2014/835791","pdf_url":"https://downloads.hindawi.com/journals/jam/2014/835791.pdf","source":{"id":"https://openalex.org/S190082376","display_name":"Journal of Applied Mathematics","issn_l":"1110-757X","issn":["1110-757X","1687-0042"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Applied Mathematics","raw_type":"journal-article"},{"id":"pmh:oai:CULeuclid:euclid.jam/1412177993","is_oa":false,"landing_page_url":"http://projecteuclid.org/euclid.jam/1412177993","pdf_url":null,"source":{"id":"https://openalex.org/S4306400787","display_name":"Project Euclid (Cornell University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:RePEc:hin:jnljam:835791","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/JAM/2014/835791.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"},{"id":"pmh:oai:doaj.org/article:d387c40733ae4b6f816b491ac6b6399a","is_oa":true,"landing_page_url":"https://doaj.org/article/d387c40733ae4b6f816b491ac6b6399a","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":"Journal of Applied Mathematics, Vol 2014 (2014)","raw_type":"article"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/87598","is_oa":true,"landing_page_url":"https://hdl.handle.net/10356/87598","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"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":null,"raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1155/2014/835791","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2014/835791","pdf_url":"https://downloads.hindawi.com/journals/jam/2014/835791.pdf","source":{"id":"https://openalex.org/S190082376","display_name":"Journal of Applied Mathematics","issn_l":"1110-757X","issn":["1110-757X","1687-0042"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Applied Mathematics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G222439991","display_name":null,"funder_award_id":"2011AA05A107","funder_id":"https://openalex.org/F4320335773","funder_display_name":"National High-tech Research and Development Program"}],"funders":[{"id":"https://openalex.org/F4320324856","display_name":"Southeast University","ror":"https://ror.org/04ct4d772"},{"id":"https://openalex.org/F4320335773","display_name":"National High-tech Research and Development Program","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1974845639.pdf","grobid_xml":"https://content.openalex.org/works/W1974845639.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W3750276","https://openalex.org/W5606438","https://openalex.org/W228380312","https://openalex.org/W1517392359","https://openalex.org/W1517808374","https://openalex.org/W1563088657","https://openalex.org/W1596717185","https://openalex.org/W1906483060","https://openalex.org/W1967333634","https://openalex.org/W1981552604","https://openalex.org/W1984703120","https://openalex.org/W1985676617","https://openalex.org/W2000272923","https://openalex.org/W2011972735","https://openalex.org/W2021244158","https://openalex.org/W2024692966","https://openalex.org/W2048086440","https://openalex.org/W2052025260","https://openalex.org/W2053226616","https://openalex.org/W2074511771","https://openalex.org/W2084895031","https://openalex.org/W2087675932","https://openalex.org/W2088474334","https://openalex.org/W2092944019","https://openalex.org/W2108587916","https://openalex.org/W2113238782","https://openalex.org/W2128741405","https://openalex.org/W2130444042","https://openalex.org/W2132984323","https://openalex.org/W2137226992","https://openalex.org/W2138745909","https://openalex.org/W2139212933","https://openalex.org/W2139809490","https://openalex.org/W2144593187","https://openalex.org/W2146842127","https://openalex.org/W2153635508","https://openalex.org/W2158143121","https://openalex.org/W2168138569","https://openalex.org/W3104887532"],"related_works":["https://openalex.org/W3209652703","https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2766585573"],"abstract_inverted_index":{"The":[0,51],"purpose":[1],"of":[2,55,68,137],"this":[3,56],"paper":[4,35,57],"is":[5,14,21,110,171],"to":[6,37,45,133],"investigate":[7,134],"the":[8,47,86,94,120,135,163,168],"short-term":[9],"wind":[10,28,30],"power":[11,157],"forecasting.":[12],"STWPF":[13,43,109],"a":[15,39,172],"typically":[16],"complex":[17],"issue,":[18],"because":[19],"it":[20],"affected":[22],"by":[23,103,112],"many":[24],"factors":[25],"such":[26,72],"as":[27,59,73],"speed,":[29],"direction,":[31],"and":[32,44,78,93,98,119,150,175],"humidity.":[33],"This":[34],"attempts":[36],"provide":[38],"reference":[40],"strategy":[41],"for":[42,156],"solve":[46],"problems":[48],"in":[49],"existence.":[50],"two":[52,144],"main":[53],"contributions":[54],"are":[58,101,125,159],"follows.":[60],"(1)":[61],"In":[62,131,161],"data":[63,71,80],"preprocessing,":[64],"each":[65],"encountered":[66],"problem":[67],"employed":[69],"real":[70],"irrelevant,":[74],"outliers,":[75],"missing":[76],"value,":[77],"noisy":[79],"has":[81,90],"been":[82,91],"taken":[83],"into":[84],"account,":[85],"corresponding":[87],"reasonable":[88],"processing":[89],"given,":[92],"input":[95],"variable":[96],"selection":[97],"order":[99,132],"estimation":[100],"investigated":[102,111],"Partial":[104],"least":[105],"squares":[106],"technique.":[107],"(2)":[108],"multiscale":[113,148,169],"support":[114],"vector":[115],"regression":[116],"(SVR)":[117],"technique,":[118],"parameters":[121],"associated":[122],"with":[123],"SVR":[124,149,170],"optimized":[126],"based":[127],"on":[128],"Grid-search":[129],"method.":[130],"performance":[136],"proposed":[138],"strategy,":[139],"forecasting":[140,146],"results":[141],"comparison":[142],"between":[143],"different":[145],"models,":[147],"multilayer":[151],"perceptron":[152],"neural":[153],"network":[154],"applied":[155],"forecasts,":[158],"presented.":[160],"addition,":[162],"error":[164],"evaluation":[165],"demonstrates":[166],"that":[167],"robust,":[173],"precise,":[174],"effective":[176],"approach.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
