{"id":"https://openalex.org/W2968973690","doi":"https://doi.org/10.1109/isgt.2019.8791654","title":"Commercial Building Load Forecasts with Artificial Neural Network","display_name":"Commercial Building Load Forecasts with Artificial Neural Network","publication_year":2019,"publication_date":"2019-02-01","ids":{"openalex":"https://openalex.org/W2968973690","doi":"https://doi.org/10.1109/isgt.2019.8791654","mag":"2968973690"},"language":"en","primary_location":{"id":"doi:10.1109/isgt.2019.8791654","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt.2019.8791654","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Power &amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)","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/A5058506660","display_name":"Zejia Jing","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zejia Jing","raw_affiliation_strings":["Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA"],"affiliations":[{"raw_affiliation_string":"Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104086982","display_name":"Mengmeng Cai","orcid":"https://orcid.org/0000-0002-8781-4204"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengmeng Cai","raw_affiliation_strings":["Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA"],"affiliations":[{"raw_affiliation_string":"Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090636432","display_name":"Manisa Pipattanasomporn","orcid":"https://orcid.org/0000-0003-1381-601X"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manisa Pipattanasomporn","raw_affiliation_strings":["Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA"],"affiliations":[{"raw_affiliation_string":"Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068719579","display_name":"Saifur Rahman","orcid":"https://orcid.org/0000-0003-0652-1002"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saifur Rahman","raw_affiliation_strings":["Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA"],"affiliations":[{"raw_affiliation_string":"Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073407849","display_name":"Raghavan Kothandaraman","orcid":null},"institutions":[{"id":"https://openalex.org/I87828566","display_name":"Edison International (United States)","ror":"https://ror.org/03q0f4n26","country_code":"US","type":"company","lineage":["https://openalex.org/I87828566"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raghavan Kothandaraman","raw_affiliation_strings":["Commonwealth Edison Company (ComEd), Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Commonwealth Edison Company (ComEd), Chicago, IL, USA","institution_ids":["https://openalex.org/I87828566"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034393145","display_name":"Ahmadreza Malekpour","orcid":null},"institutions":[{"id":"https://openalex.org/I87828566","display_name":"Edison International (United States)","ror":"https://ror.org/03q0f4n26","country_code":"US","type":"company","lineage":["https://openalex.org/I87828566"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmadreza Malekpour","raw_affiliation_strings":["Commonwealth Edison Company (ComEd), Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Commonwealth Edison Company (ComEd), Chicago, IL, USA","institution_ids":["https://openalex.org/I87828566"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069254734","display_name":"Esa Aleksi Paaso","orcid":"https://orcid.org/0000-0002-3980-9267"},"institutions":[{"id":"https://openalex.org/I87828566","display_name":"Edison International (United States)","ror":"https://ror.org/03q0f4n26","country_code":"US","type":"company","lineage":["https://openalex.org/I87828566"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Esa Aleksi Paaso","raw_affiliation_strings":["Commonwealth Edison Company (ComEd), Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Commonwealth Edison Company (ComEd), Chicago, IL, USA","institution_ids":["https://openalex.org/I87828566"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074199539","display_name":"Shay Bahramirad","orcid":"https://orcid.org/0000-0002-4844-3447"},"institutions":[{"id":"https://openalex.org/I87828566","display_name":"Edison International (United States)","ror":"https://ror.org/03q0f4n26","country_code":"US","type":"company","lineage":["https://openalex.org/I87828566"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shay Bahramirad","raw_affiliation_strings":["Commonwealth Edison Company (ComEd), Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Commonwealth Edison Company (ComEd), Chicago, IL, USA","institution_ids":["https://openalex.org/I87828566"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5058506660"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":0.8346,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.74086967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9997000098228455,"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":0.9997000098228455,"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9929999709129333,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.8104796409606934},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.718377947807312},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6470277905464172},{"id":"https://openalex.org/keywords/levenberg\u2013marquardt-algorithm","display_name":"Levenberg\u2013Marquardt algorithm","score":0.6306391358375549},{"id":"https://openalex.org/keywords/hvac","display_name":"HVAC","score":0.5814386606216431},{"id":"https://openalex.org/keywords/electrical-load","display_name":"Electrical load","score":0.5679953694343567},{"id":"https://openalex.org/keywords/cooling-load","display_name":"Cooling load","score":0.52744060754776},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5017976760864258},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4442249834537506},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.43489694595336914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3810814619064331},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34983009099960327},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20667335391044617},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13995009660720825},{"id":"https://openalex.org/keywords/air-conditioning","display_name":"Air conditioning","score":0.1394200325012207},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.0925430953502655}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.8104796409606934},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.718377947807312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470277905464172},{"id":"https://openalex.org/C87578567","wikidata":"https://www.wikidata.org/wiki/Q1426494","display_name":"Levenberg\u2013Marquardt algorithm","level":3,"score":0.6306391358375549},{"id":"https://openalex.org/C122346748","wikidata":"https://www.wikidata.org/wiki/Q1798773","display_name":"HVAC","level":3,"score":0.5814386606216431},{"id":"https://openalex.org/C77715397","wikidata":"https://www.wikidata.org/wiki/Q931447","display_name":"Electrical load","level":3,"score":0.5679953694343567},{"id":"https://openalex.org/C2781099182","wikidata":"https://www.wikidata.org/wiki/Q24963825","display_name":"Cooling load","level":3,"score":0.52744060754776},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5017976760864258},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4442249834537506},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.43489694595336914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3810814619064331},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34983009099960327},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20667335391044617},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13995009660720825},{"id":"https://openalex.org/C103742991","wikidata":"https://www.wikidata.org/wiki/Q173725","display_name":"Air conditioning","level":2,"score":0.1394200325012207},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0925430953502655},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/isgt.2019.8791654","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isgt.2019.8791654","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Power &amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1971330976","https://openalex.org/W1978602460","https://openalex.org/W2070342971","https://openalex.org/W2074475184","https://openalex.org/W2083266970","https://openalex.org/W2114534220","https://openalex.org/W2156302255","https://openalex.org/W2158884660","https://openalex.org/W2318502288","https://openalex.org/W2586259521","https://openalex.org/W2729160391","https://openalex.org/W2739283086","https://openalex.org/W2762726101","https://openalex.org/W6643149526","https://openalex.org/W6683166055","https://openalex.org/W6699590210"],"related_works":["https://openalex.org/W2207919472","https://openalex.org/W3000938991","https://openalex.org/W267418541","https://openalex.org/W2088519771","https://openalex.org/W4210577596","https://openalex.org/W2014565402","https://openalex.org/W1565720114","https://openalex.org/W2082262584","https://openalex.org/W4381550084","https://openalex.org/W2334633986"],"abstract_inverted_index":{"This":[0],"paper":[1,43],"presents":[2],"an":[3],"Artificial":[4],"Neural":[5],"Network":[6],"(ANN)-based":[7],"building-level":[8],"hourly":[9],"electrical":[10],"load":[11,33,47,61,67,138,148],"forecasting":[12,62,103,129],"method":[13],"that":[14,91],"takes":[15],"into":[16],"account":[17],"HVAC":[18],"set":[19],"points":[20],"as":[21],"one":[22],"of":[23,71,102,121],"the":[24,30,56,59,65,72,92,97,122],"input":[25],"parameters,":[26],"in":[27,41,100,114],"addition":[28],"to":[29,52],"historical":[31],"building":[32,113],"and":[34,54,58,85,140],"outdoor":[35],"weather":[36],"data.":[37],"The":[38,128],"data":[39],"presented":[40,118],"this":[42],"deal":[44],"with":[45],"cooling":[46],"only.":[48],"ANN":[49],"is":[50,117,131],"used":[51],"train":[53],"test":[55],"dataset,":[57],"ANN-based":[60,124],"model":[63],"provides":[64],"predicted":[66],"for":[68,136,145],"each":[69],"hour":[70],"day.":[73],"Three":[74],"training":[75],"algorithms":[76],"are":[77,126],"explored,":[78],"including":[79],"Levenberg-Marquardt,":[80],"Scaled":[81],"Conjugate":[82],"gradient":[83],"back-propagation":[84],"Bayesian":[86],"Regularization":[87],"(BR).":[88],"Findings":[89],"indicate":[90],"BR-based":[93],"neural":[94],"network":[95],"offers":[96],"best":[98],"performance":[99],"terms":[101],"accuracy.":[104],"In":[105],"addition,":[106],"a":[107,111],"case":[108],"study":[109],"using":[110],"commercial":[112],"Chicago,":[115],"Illinois":[116],"where":[119],"performances":[120],"developed":[123],"models":[125],"compared.":[127],"error":[130],"around":[132,141],"5%":[133],"or":[134,143],"less":[135,144],"hour-ahead":[137],"forecasting,":[139],"8%":[142],"12-hour":[146],"ahead":[147],"forecasting.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
