{"id":"https://openalex.org/W3142010597","doi":"https://doi.org/10.1109/icbaie52039.2021.9389896","title":"Short Term Load Forecasting Based on BFA-DRESN Algorithm","display_name":"Short Term Load Forecasting Based on BFA-DRESN Algorithm","publication_year":2021,"publication_date":"2021-03-26","ids":{"openalex":"https://openalex.org/W3142010597","doi":"https://doi.org/10.1109/icbaie52039.2021.9389896","mag":"3142010597"},"language":"en","primary_location":{"id":"doi:10.1109/icbaie52039.2021.9389896","doi":"https://doi.org/10.1109/icbaie52039.2021.9389896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbaie52039.2021.9389896","pdf_url":null,"source":{"id":"https://openalex.org/S4363608182","display_name":"International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5044923788","display_name":"Jianan Yuan","orcid":"https://orcid.org/0000-0002-5825-3305","observed_orcids":["https://orcid.org/0000-0002-5825-3305"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianan Yuan","raw_affiliation_strings":["Beijing SmartChip Microelectronics Company Limited, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing SmartChip Microelectronics Company Limited, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100693236","display_name":"Wenbin Chen","orcid":"https://orcid.org/0000-0001-8305-0764","observed_orcids":["https://orcid.org/0000-0001-8305-0764","https://orcid.org/0009-0003-5254-8502"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenbin Chen","raw_affiliation_strings":["Beijing SmartChip Microelectronics Company Limited, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing SmartChip Microelectronics Company Limited, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040862135","display_name":"Anqin Luo","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anqin Luo","raw_affiliation_strings":["Beijing SmartChip Microelectronics Company Limited, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing SmartChip Microelectronics Company Limited, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110322854","display_name":"Chao Huo","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chao Huo","raw_affiliation_strings":["Beijing SmartChip Microelectronics Company Limited, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing SmartChip Microelectronics Company Limited, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030432753","display_name":"Shuaiying Ma","orcid":"https://orcid.org/0009-0000-0168-2590","observed_orcids":["https://orcid.org/0009-0000-0168-2590"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuaiying Ma","raw_affiliation_strings":["Beijing SmartChip Microelectronics Company Limited, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing SmartChip Microelectronics Company Limited, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1606,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70594079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"114","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9818999767303467,"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":0.9818999767303467,"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":0.002899999963119626,"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/T12451","display_name":"Smart Grid and Power Systems","score":0.0012000000569969416,"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/short-term-load-forecasting","display_name":"short-term load forecasting","score":0.9819999933242798},{"id":"https://openalex.org/keywords/echo-state-networks","display_name":"echo state networks","score":0.9860000014305115},{"id":"https://openalex.org/keywords/bacterial-foraging-optimization","display_name":"bacterial foraging optimization","score":0.9700000286102295},{"id":"https://openalex.org/keywords/parameter-optimization","display_name":"parameter optimization","score":0.5590000152587891},{"id":"https://openalex.org/keywords/smart-grid","display_name":"smart grid","score":0.6740000247955322},{"id":"https://openalex.org/keywords/smart-meters","display_name":"smart meters","score":0.6940000057220459},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.746999979019165},{"id":"https://openalex.org/keywords/time-series-forecasting","display_name":"time series forecasting","score":0.7599999904632568}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7727901339530945},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.5648787021636963},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5531071424484253},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5184561610221863},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.49111196398735046},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.4888004958629608},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.447332501411438},{"id":"https://openalex.org/C172025690","wikidata":"https://www.wikidata.org/wiki/Q5332763","display_name":"Echo state network","level":4,"score":0.4409596025943756},{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.4280274510383606},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42022615671157837},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4146053194999695},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3661049008369446},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3397732675075531},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.23185193538665771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21626406908035278},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17018058896064758},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15808480978012085},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13808736205101013},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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},{"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/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/icbaie52039.2021.9389896","doi":"https://doi.org/10.1109/icbaie52039.2021.9389896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbaie52039.2021.9389896","pdf_url":null,"source":{"id":"https://openalex.org/S4363608182","display_name":"International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8970999717712402,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"},{"score":0.75,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2803305036","https://openalex.org/W2884378264","https://openalex.org/W2917365054","https://openalex.org/W2920867407","https://openalex.org/W2945437135","https://openalex.org/W2996159937","https://openalex.org/W3004384276","https://openalex.org/W3013553091","https://openalex.org/W3014690401"],"related_works":["https://openalex.org/W3111334809","https://openalex.org/W3011358785","https://openalex.org/W4387412815","https://openalex.org/W3048899449","https://openalex.org/W2805797750","https://openalex.org/W7167457888","https://openalex.org/W3215742260","https://openalex.org/W3017013745","https://openalex.org/W4318603362","https://openalex.org/W3197500874"],"abstract_inverted_index":{"With":[0],"the":[1,53,58,81,106,123,126,134,140,150,155,167,178,181,192,201,207],"in-depth":[2],"development":[3],"of":[4,6,12,14,23,48,66,83,105,128,152,180],"Internet":[5,13,47],"things":[7,15,49],"technology,":[8],"a":[9,37,63],"large":[10,64],"number":[11],"sensing":[16],"devices":[17],"are":[18,189],"deployed":[19],"in":[20],"various":[21],"environments":[22],"power":[24,32,44,59,118],"grid.":[25],"Smart":[26],"meters":[27],"can":[28,76,204],"continuously":[29],"obtain":[30],"users'":[31],"consumption":[33],"parameters":[34,179],"according":[35],"to":[36,43,79,117,149],"certain":[38],"frequency,":[39],"and":[40,101,171,177],"transmit":[41],"them":[42],"companies":[45],"through":[46],"communication":[50],"technology.":[51],"In":[52],"existing":[54,107],"smart":[55],"grid":[56,60],"architecture,":[57],"system":[61],"produces":[62],"amount":[65],"related":[67],"data.":[68],"Based":[69],"on":[70],"these":[71],"data,":[72],"more":[73],"useful":[74],"information":[75,173],"be":[77],"mined":[78],"improve":[80,206],"accuracy":[82],"load":[84,87,119,153,160,169],"forecasting.":[85,120],"However,":[86],"forecasting":[88,110,135,161],"is":[89,163],"affected":[90],"by":[91,165,191],"many":[92],"complex":[93],"factors,":[94],"weather,":[95],"date":[96],"type,":[97],"user":[98],"behavior":[99],"mode":[100],"so":[102],"on.":[103],"Most":[104],"time":[108],"series":[109],"methods":[111],"have":[112],"some":[113],"limitations":[114],"when":[115],"applied":[116],"Aiming":[121],"at":[122],"problem":[124],"that":[125,200],"structure":[127],"traditional":[129],"ESN":[130],"reserve":[131,146,187],"pool":[132],"affects":[133],"performance;":[136],"this":[137],"paper":[138],"adopts":[139],"echo":[141,182],"state":[142,183],"network":[143,158,184],"with":[144,185],"double":[145,186],"pools.":[147],"According":[148],"demand":[151],"forecasting,":[154],"depth":[156],"neural":[157],"intelligent":[159],"model":[162],"constructed":[164],"using":[166],"historical":[168],"data":[170],"multi-dimensional":[172],"such":[174],"as":[175],"environment,":[176],"pools":[188],"optimized":[190],"bacterial":[193],"foraging":[194],"algorithm.":[195],"The":[196],"simulation":[197],"results":[198],"show":[199],"proposed":[202],"BFA-DRESN":[203],"effectively":[205],"prediction":[208],"accuracy.":[209]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2021-04-13T00:00:00"}
