{"id":"https://openalex.org/W4399729007","doi":"https://doi.org/10.1109/syscon61195.2024.10553600","title":"Load Forecasting using GNN-LSTM Attention Mechanism with Low-Frequency Data","display_name":"Load Forecasting using GNN-LSTM Attention Mechanism with Low-Frequency Data","publication_year":2024,"publication_date":"2024-04-15","ids":{"openalex":"https://openalex.org/W4399729007","doi":"https://doi.org/10.1109/syscon61195.2024.10553600"},"language":"en","primary_location":{"id":"doi:10.1109/syscon61195.2024.10553600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/syscon61195.2024.10553600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Systems Conference (SysCon)","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/A5104329416","display_name":"Amanie Azzam","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Amanie Azzam","raw_affiliation_strings":["Concordia Univerity,Department of Electrical and Computer Engineering,Montreal,QC,Canada","Department of Electrical and Computer Engineering, Concordia Univerity, Montreal, QC, Canada"],"affiliations":[{"raw_affiliation_string":"Concordia Univerity,Department of Electrical and Computer Engineering,Montreal,QC,Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia Univerity, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092489718","display_name":"Saba Sanami","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Saba Sanami","raw_affiliation_strings":["Concordia Univerity,Department of Electrical and Computer Engineering,Montreal,QC,Canada","Department of Electrical and Computer Engineering, Concordia Univerity, Montreal, QC, Canada"],"affiliations":[{"raw_affiliation_string":"Concordia Univerity,Department of Electrical and Computer Engineering,Montreal,QC,Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia Univerity, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023864111","display_name":"Amir G. Aghdam","orcid":"https://orcid.org/0000-0001-5180-0508"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Amir G. Aghdam","raw_affiliation_strings":["Concordia Univerity,Department of Electrical and Computer Engineering,Montreal,QC,Canada","Department of Electrical and Computer Engineering, Concordia Univerity, Montreal, QC, Canada"],"affiliations":[{"raw_affiliation_string":"Concordia Univerity,Department of Electrical and Computer Engineering,Montreal,QC,Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia Univerity, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5104329416"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":1.0334,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75896071,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"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":0.9994999766349792,"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":0.9994999766349792,"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":0.9922999739646912,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.98580002784729,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7306624054908752},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.6167482733726501},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3810555934906006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7306624054908752},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.6167482733726501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3810555934906006},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/syscon61195.2024.10553600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/syscon61195.2024.10553600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Systems Conference (SysCon)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1272474793","https://openalex.org/W2784248148","https://openalex.org/W2908947568","https://openalex.org/W3102927640","https://openalex.org/W3117492306","https://openalex.org/W3163620325","https://openalex.org/W3198120912","https://openalex.org/W3198933754","https://openalex.org/W3215514190","https://openalex.org/W4210840942","https://openalex.org/W4226318544","https://openalex.org/W4290755293","https://openalex.org/W4328112705","https://openalex.org/W4362681817","https://openalex.org/W4379055600","https://openalex.org/W4381509770","https://openalex.org/W4400077402","https://openalex.org/W6858637227"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382997850","https://openalex.org/W2382290278"],"abstract_inverted_index":{"Non-intrusive":[0],"load":[1,169],"monitoring":[2],"(NILM)":[3],"in":[4,71,167],"smart":[5],"home":[6],"applications":[7],"provides":[8],"insights":[9],"into":[10,142],"household":[11,44,131,176],"energy":[12],"usage":[13,143],"patterns.":[14,100],"This":[15],"paper":[16],"presents":[17],"a":[18,22,27,75,79,126],"NILM":[19],"methodology":[20],"using":[21],"graph":[23,76],"neural":[24],"network":[25,93],"(GNN),":[26],"long":[28],"short-term":[29],"memory":[30],"(LSTM)":[31],"network,":[32],"and":[33,61,134,145],"an":[34],"attention":[35,102],"mechanism.":[36],"It":[37],"also":[38],"investigates":[39],"the":[40,49,56,67,72,84,105,110,117,153,161,164],"temporal":[41,99,154],"correlation":[42],"between":[43,59,69,156],"appliances.":[45,157],"The":[46,101],"objective":[47],"of":[48,74,129,163],"proposed":[50,165],"learning-based":[51],"approach":[52,166],"is":[53,94],"to":[54,97,114,124],"represent":[55],"complex":[57],"dependencies":[58],"appliances":[60,70,132],"their":[62],"power":[63,146],"usage.":[64],"We":[65,120],"capture":[66,98],"interaction":[68],"form":[73],"by":[77,149,171],"integrating":[78],"GNN,":[80],"which":[81],"serves":[82],"as":[83],"foundation":[85],"for":[86],"more":[87],"effective":[88],"feature":[89],"extraction.":[90],"An":[91],"LSTM":[92],"then":[95],"implemented":[96],"process,":[103],"on":[104,109],"other":[106],"hand,":[107],"focuses":[108],"most":[111],"crucial":[112],"information":[113,151],"further":[115],"boost":[116],"prediction":[118,170],"performance.":[119],"utilize":[121],"heat":[122],"maps":[123],"develop":[125],"better":[127],"understanding":[128],"how":[130],"perform":[133],"correlate":[135],"over":[136],"time.":[137],"These":[138],"visualizations":[139],"provide":[140],"insight":[141],"patterns":[144,174],"consumption":[147],"sequences":[148],"giving":[150],"about":[152],"interconnections":[155],"Experimental":[158],"results":[159],"demonstrate":[160],"effectiveness":[162],"accurate":[168],"uncovering":[172],"hidden":[173],"within":[175],"appliance":[177],"data.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
