{"id":"https://openalex.org/W4391094368","doi":"https://doi.org/10.1109/iciscae59047.2023.10393092","title":"Combined heat and power load prediction based on optimized GRU neural network","display_name":"Combined heat and power load prediction based on optimized GRU neural network","publication_year":2023,"publication_date":"2023-09-23","ids":{"openalex":"https://openalex.org/W4391094368","doi":"https://doi.org/10.1109/iciscae59047.2023.10393092"},"language":"en","primary_location":{"id":"doi:10.1109/iciscae59047.2023.10393092","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iciscae59047.2023.10393092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 6th International Conference on Information Systems and Computer Aided Education (ICISCAE)","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/A5044623020","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-4637-6308"},"institutions":[{"id":"https://openalex.org/I121691239","display_name":"Beihua University","ror":"https://ror.org/013jjp941","country_code":"CN","type":"education","lineage":["https://openalex.org/I121691239"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Beihua University,Jilin,China","Beihua University, Jilin, China"],"affiliations":[{"raw_affiliation_string":"Beihua University,Jilin,China","institution_ids":["https://openalex.org/I121691239"]},{"raw_affiliation_string":"Beihua University, Jilin, China","institution_ids":["https://openalex.org/I121691239"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086596126","display_name":"Jikun Yang","orcid":"https://orcid.org/0000-0003-1663-8693"},"institutions":[{"id":"https://openalex.org/I121691239","display_name":"Beihua University","ror":"https://ror.org/013jjp941","country_code":"CN","type":"education","lineage":["https://openalex.org/I121691239"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jikun Yang","raw_affiliation_strings":["Beihua University,Jilin,China","Beihua University, Jilin, China"],"affiliations":[{"raw_affiliation_string":"Beihua University,Jilin,China","institution_ids":["https://openalex.org/I121691239"]},{"raw_affiliation_string":"Beihua University, Jilin, China","institution_ids":["https://openalex.org/I121691239"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062349713","display_name":"Jisheng Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I121691239","display_name":"Beihua University","ror":"https://ror.org/013jjp941","country_code":"CN","type":"education","lineage":["https://openalex.org/I121691239"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jisheng Xing","raw_affiliation_strings":["Beihua University,Jilin,China","Beihua University, Jilin, China"],"affiliations":[{"raw_affiliation_string":"Beihua University,Jilin,China","institution_ids":["https://openalex.org/I121691239"]},{"raw_affiliation_string":"Beihua University, Jilin, China","institution_ids":["https://openalex.org/I121691239"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100663605","display_name":"Lu Wang","orcid":"https://orcid.org/0000-0002-4863-119X"},"institutions":[{"id":"https://openalex.org/I121691239","display_name":"Beihua University","ror":"https://ror.org/013jjp941","country_code":"CN","type":"education","lineage":["https://openalex.org/I121691239"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Wang","raw_affiliation_strings":["Beihua University,Jilin,China","Beihua University, Jilin, China"],"affiliations":[{"raw_affiliation_string":"Beihua University,Jilin,China","institution_ids":["https://openalex.org/I121691239"]},{"raw_affiliation_string":"Beihua University, Jilin, China","institution_ids":["https://openalex.org/I121691239"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044623020"],"corresponding_institution_ids":["https://openalex.org/I121691239"],"apc_list":null,"apc_paid":null,"fwci":0.2836,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57369499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"38","issue":null,"first_page":"1161","last_page":"1165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9991999864578247,"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":0.9991999864578247,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9851999878883362,"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/T10320","display_name":"Neural Networks and Applications","score":0.9811000227928162,"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/cogeneration","display_name":"Cogeneration","score":0.9220315217971802},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7060993909835815},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.6736539602279663},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6347107291221619},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.5141516327857971},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.4967804551124573},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4730262756347656},{"id":"https://openalex.org/keywords/load-profile","display_name":"Load profile","score":0.4285218119621277},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2705308496952057},{"id":"https://openalex.org/keywords/electricity-generation","display_name":"Electricity generation","score":0.2655855417251587},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22300586104393005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1596783995628357},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.13797181844711304}],"concepts":[{"id":"https://openalex.org/C2776756539","wikidata":"https://www.wikidata.org/wiki/Q221620","display_name":"Cogeneration","level":4,"score":0.9220315217971802},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7060993909835815},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.6736539602279663},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6347107291221619},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.5141516327857971},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.4967804551124573},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4730262756347656},{"id":"https://openalex.org/C2777908891","wikidata":"https://www.wikidata.org/wiki/Q1806775","display_name":"Load profile","level":3,"score":0.4285218119621277},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2705308496952057},{"id":"https://openalex.org/C423512","wikidata":"https://www.wikidata.org/wiki/Q383973","display_name":"Electricity generation","level":3,"score":0.2655855417251587},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22300586104393005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1596783995628357},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.13797181844711304},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iciscae59047.2023.10393092","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iciscae59047.2023.10393092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 6th International Conference on Information Systems and Computer Aided Education (ICISCAE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8700000047683716,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337495","display_name":"Technology Development","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2571945220","https://openalex.org/W2889480665","https://openalex.org/W3084139625"],"related_works":["https://openalex.org/W1998119461","https://openalex.org/W2359988301","https://openalex.org/W2601500142","https://openalex.org/W2495363594","https://openalex.org/W1964989542","https://openalex.org/W1535035594","https://openalex.org/W2911615494","https://openalex.org/W2522673987","https://openalex.org/W93004457","https://openalex.org/W115595012"],"abstract_inverted_index":{"Load":[0],"forecasting":[1],"is":[2,43,98,137],"the":[3,22,26,29,36,53,65,69,87,104,114,124,129,132,140,143,149,153,158,166],"basis":[4],"for":[5,45,80,93],"improved":[6],"energy":[7],"utilization":[8],"and":[9,28,83,103,118,122,135,148,164],"optimal":[10],"dispatch":[11],"of":[12,17,25,31,39,68,86,131,142,168],"cogeneration":[13,40,70],"systems.":[14],"The":[15],"accuracy":[16,167],"its":[18],"predictions":[19],"greatly":[20],"affects":[21],"operating":[23],"performance":[24],"system":[27],"cost":[30],"thermal":[32,145],"power":[33,146],"plants.":[34],"With":[35],"large-scale":[37],"use":[38],"units,":[41],"it":[42],"difficult":[44],"a":[46,61,91],"single":[47],"load":[48,81,169],"forecast":[49],"to":[50],"accurately":[51],"reflect":[52],"coupling":[54,159],"characteristics":[55,160],"between":[56,161],"thermoelectric":[57,162],"loads,":[58,163],"which":[59],"has":[60],"certain":[62],"impact":[63],"on":[64],"accurate":[66],"operation":[67],"system.":[71],"At":[72],"present,":[73],"artificial":[74],"intelligence":[75],"algorithms":[76],"are":[77,108,126],"basically":[78],"used":[79],"forecasting,":[82],"in":[84,100,110],"view":[85],"previous":[88],"algorithm":[89,136],"comparison,":[90],"model":[92,155],"optimizing":[94],"GRU":[95,105],"neural":[96,106],"networks":[97,107],"proposed":[99,133,154],"this":[101],"paper,":[102],"connected":[109,120],"parallel,":[111],"processed":[112],"through":[113],"corresponding":[115],"dropout":[116],"layer":[117],"fully":[119,156],"layer,":[121],"finally":[123],"results":[125,150],"merged.":[127],"Finally,":[128],"feasibility":[130],"method":[134],"verified":[138],"by":[139],"data":[141],"actual":[144],"plant,":[147],"show":[151],"that":[152],"learns":[157],"improves":[165],"prediction.":[170]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
