{"id":"https://openalex.org/W4372346121","doi":"https://doi.org/10.1109/icassp49357.2023.10096002","title":"SADI: A Self-Adaptive Decomposed Interpretable Framework for Electric Load Forecasting Under Extreme Events","display_name":"SADI: A Self-Adaptive Decomposed Interpretable Framework for Electric Load Forecasting Under Extreme Events","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372346121","doi":"https://doi.org/10.1109/icassp49357.2023.10096002"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10096002","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5010140106","display_name":"Hengbo Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hengbo Liu","raw_affiliation_strings":["Alibaba Group,DAMO Academy,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,DAMO Academy,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035357260","display_name":"Ziqing Ma","orcid":"https://orcid.org/0000-0003-1567-5054"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziqing Ma","raw_affiliation_strings":["Alibaba Group,DAMO Academy,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,DAMO Academy,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072947305","display_name":"Linxiao Yang","orcid":"https://orcid.org/0000-0001-9558-7163"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linxiao Yang","raw_affiliation_strings":["Alibaba Group,DAMO Academy,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,DAMO Academy,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101890076","display_name":"Tian Zhou","orcid":"https://orcid.org/0000-0003-1789-5413"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Zhou","raw_affiliation_strings":["Alibaba Group,DAMO Academy,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,DAMO Academy,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101640515","display_name":"Rui Xia","orcid":"https://orcid.org/0000-0002-6899-6735"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Xia","raw_affiliation_strings":["Alibaba Group,DAMO Academy,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,DAMO Academy,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364888","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0001-7001-9573"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Yi Wang","raw_affiliation_strings":["The University of Hong Kong,Hong Kong,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Hong Kong,China","institution_ids":["https://openalex.org/I177725633","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048346353","display_name":"Qingsong Wen","orcid":"https://orcid.org/0000-0003-4516-2524"},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qingsong Wen","raw_affiliation_strings":["Alibaba Group,DAMO Academy,Bellevue,US"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,DAMO Academy,Bellevue,US","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068194653","display_name":"Liang Sun","orcid":"https://orcid.org/0000-0001-8407-2201"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]},{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Sun","raw_affiliation_strings":["Alibaba Group,DAMO Academy,Bellevue,US"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,DAMO Academy,Bellevue,US","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5010140106"],"corresponding_institution_ids":["https://openalex.org/I45928872"],"apc_list":null,"apc_paid":null,"fwci":1.7356,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84376375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"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":1.0,"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":1.0,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.9878000020980835,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.9052723050117493},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.6515161991119385},{"id":"https://openalex.org/keywords/electrical-load","display_name":"Electrical load","score":0.6388024687767029},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5776212215423584},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5342974066734314},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.43178096413612366},{"id":"https://openalex.org/keywords/extreme-weather","display_name":"Extreme weather","score":0.4179079532623291},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4037018418312073},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.27663156390190125},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1724173128604889},{"id":"https://openalex.org/keywords/climate-change","display_name":"Climate change","score":0.0736478865146637}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9052723050117493},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.6515161991119385},{"id":"https://openalex.org/C77715397","wikidata":"https://www.wikidata.org/wiki/Q931447","display_name":"Electrical load","level":3,"score":0.6388024687767029},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5776212215423584},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5342974066734314},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.43178096413612366},{"id":"https://openalex.org/C205537798","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Extreme weather","level":3,"score":0.4179079532623291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4037018418312073},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.27663156390190125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1724173128604889},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.0736478865146637},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10096002","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10096002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W70001371","https://openalex.org/W1919803322","https://openalex.org/W2044742906","https://openalex.org/W2049751389","https://openalex.org/W2060071843","https://openalex.org/W2064675550","https://openalex.org/W2103504194","https://openalex.org/W2149033360","https://openalex.org/W2768348081","https://openalex.org/W2950418200","https://openalex.org/W3043193240","https://openalex.org/W3080957353","https://openalex.org/W3083510345","https://openalex.org/W3171322015","https://openalex.org/W3180281962","https://openalex.org/W3200130209","https://openalex.org/W4245295309","https://openalex.org/W4285176417","https://openalex.org/W4290945834","https://openalex.org/W6745609711","https://openalex.org/W6746224901","https://openalex.org/W6763309814","https://openalex.org/W6790920653","https://openalex.org/W6793065813","https://openalex.org/W6810637551"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W2964105430","https://openalex.org/W4388037829","https://openalex.org/W2885084305","https://openalex.org/W4200196800","https://openalex.org/W3165245835","https://openalex.org/W2093411737","https://openalex.org/W3158513142"],"abstract_inverted_index":{"Accurate":[0],"prediction":[1],"of":[2,38,158,161],"electric":[3,19,126],"load":[4,20,45,127],"is":[5,35,98,112],"crucial":[6],"in":[7,49,90,114,151,156],"power":[8],"grid":[9],"planning":[10],"and":[11,83,128,167],"management.":[12],"In":[13,62],"this":[14,63],"paper,":[15,64],"we":[16,65],"solve":[17],"the":[18,36,101,115,136,146],"forecasting":[21,34,69,152],"problem":[22],"under":[23,41,104,153],"extreme":[24,42,51,105,154],"events":[25,155],"such":[26],"as":[27],"scorching":[28],"heats.":[29],"One":[30],"challenge":[31],"for":[32,55,100,117],"accurate":[33],"lack":[37],"training":[39],"samples":[40],"conditions.":[43],"Also":[44],"usually":[46],"changes":[47],"dramatically":[48],"these":[50],"conditions,":[52],"which":[53,77],"calls":[54],"interpretable":[56],"model":[57],"to":[58,86],"make":[59],"better":[60],"decisions.":[61],"propose":[66],"a":[67],"novel":[68],"framework,":[70],"named":[71],"Self-adaptive":[72],"Decomposed":[73],"Interpretable":[74],"framework":[75,116,139],"(SaDI),":[76],"ensembles":[78],"long-term":[79],"trend,":[80,82],"short-term":[81],"period":[84],"modelings":[85],"capture":[87],"temporal":[88],"characteristics":[89],"different":[91],"components.":[92],"The":[93,120],"external":[94],"variable":[95],"triggered":[96],"loss":[97],"proposed":[99,137],"imbalanced":[102],"learning":[103],"events.":[106],"Furthermore,":[107],"Generalized":[108],"Additive":[109],"Model":[110],"(GAM)":[111],"employed":[113],"desirable":[118],"interpretability.":[119],"experiments":[121],"on":[122],"both":[123],"Central":[124],"China":[125],"public":[129],"energy":[130],"meters":[131],"from":[132],"buildings":[133],"show":[134],"that":[135],"SaDI":[138],"achieves":[140],"average":[141],"22.14%":[142],"improvement":[143],"compared":[144],"with":[145],"current":[147],"state-of-":[148],"the-art":[149],"algorithms":[150],"terms":[157],"daily":[159],"mean":[160],"normalized":[162],"RMSE.":[163],"Code,":[164],"Public":[165],"datasets,":[166],"Appendix":[168],"are":[169],"available":[170],"at:":[171],"https://doi.org/10.24433/CO.9696980.v1.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}
