{"id":"https://openalex.org/W1977681944","doi":"https://doi.org/10.1109/i2mtc.2013.6555474","title":"Hierarchical sparse learning for load forecasting in cyber-physical energy systems","display_name":"Hierarchical sparse learning for load forecasting in cyber-physical energy systems","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W1977681944","doi":"https://doi.org/10.1109/i2mtc.2013.6555474","mag":"1977681944"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc.2013.6555474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc.2013.6555474","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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/A5101019003","display_name":"Xinyao Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyao Sun","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China","Department of Precision Instruments, Tsinghua University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Precision Instruments, Tsinghua University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035550613","display_name":"Xue Wang","orcid":"https://orcid.org/0000-0003-4842-3160"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Wang","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China","Department of Precision Instruments, Tsinghua University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Precision Instruments, Tsinghua University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101572971","display_name":"Jiangwei Wu","orcid":"https://orcid.org/0000-0002-4341-5770"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangwei Wu","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China","Department of Precision Instruments, Tsinghua University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Precision Instruments, Tsinghua University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072522683","display_name":"Youda Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youda Liu","raw_affiliation_strings":["State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China","Department of Precision Instruments, Tsinghua University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Precision Instruments, Tsinghua University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101019003"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.7179,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.731562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"454","issue":null,"first_page":"533","last_page":"538"},"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/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"}},{"id":"https://openalex.org/T10603","display_name":"Smart Grid Energy Management","score":0.9847999811172485,"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/weighting","display_name":"Weighting","score":0.7155095934867859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7137466073036194},{"id":"https://openalex.org/keywords/probabilistic-forecasting","display_name":"Probabilistic forecasting","score":0.5877896547317505},{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.5616781115531921},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5455273389816284},{"id":"https://openalex.org/keywords/cyber-physical-system","display_name":"Cyber-physical system","score":0.54142165184021},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5193430185317993},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44962698221206665},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.4419700503349304},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.41471946239471436},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4142017066478729},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3908529281616211},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.2962924540042877}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7155095934867859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7137466073036194},{"id":"https://openalex.org/C122282355","wikidata":"https://www.wikidata.org/wiki/Q7246855","display_name":"Probabilistic forecasting","level":3,"score":0.5877896547317505},{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.5616781115531921},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5455273389816284},{"id":"https://openalex.org/C179768478","wikidata":"https://www.wikidata.org/wiki/Q1120057","display_name":"Cyber-physical system","level":2,"score":0.54142165184021},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5193430185317993},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44962698221206665},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.4419700503349304},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.41471946239471436},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4142017066478729},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3908529281616211},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2962924540042877},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc.2013.6555474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc.2013.6555474","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1964984358","https://openalex.org/W2001165499","https://openalex.org/W2007221293","https://openalex.org/W2017561014","https://openalex.org/W2109599521","https://openalex.org/W2121900750","https://openalex.org/W2123044680","https://openalex.org/W2127192673","https://openalex.org/W2127233871","https://openalex.org/W2135651192","https://openalex.org/W2136325969","https://openalex.org/W2304026854","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4382795578","https://openalex.org/W2355463328","https://openalex.org/W2402648945","https://openalex.org/W1431147547","https://openalex.org/W2771741613","https://openalex.org/W2055761197","https://openalex.org/W2053213469","https://openalex.org/W2057608111","https://openalex.org/W2793032185","https://openalex.org/W3107306829"],"abstract_inverted_index":{"Cyber-physical":[0],"energy":[1],"systems,":[2],"which":[3,62,82],"emerges":[4],"as":[5,99,101],"the":[6,55,59,102,115,124],"approach":[7,77,126],"for":[8,34,65,78],"integrating":[9],"physical":[10],"layers":[11],"and":[12,40,136],"control":[13],"networks,":[14],"have":[15,49],"drawn":[16],"extensively":[17],"attention":[18],"in":[19,32,37,68,91,130],"recent":[20],"years.":[21],"Electric":[22],"load":[23,46,80],"forecasting":[24,97,103],"is":[25,111],"believed":[26],"to":[27,51,93,113],"be":[28],"an":[29],"important":[30,64],"issue":[31],"CPES":[33],"its":[35],"applications":[36],"prices":[38],"determination":[39],"automatic":[41],"generation":[42],"control.":[43],"Conventional":[44],"deterministic":[45],"forecast":[47],"method":[48],"drawbacks":[50],"providing":[52],"information":[53],"about":[54],"probability":[56],"distribution":[57],"of":[58],"prediction":[60],"results,":[61,98],"are":[63],"stochastic":[66],"decision":[67],"power":[69],"systems.":[70],"This":[71],"paper":[72],"explores":[73],"a":[74,95],"hierarchical":[75],"probabilistic":[76],"short-term":[79],"forecast,":[81],"combines":[83],"sparse":[84],"Bayesian":[85],"learning":[86],"with":[87,132],"empirical":[88],"mode":[89],"decomposition,":[90],"order":[92],"obtain":[94],"componential":[96,140],"well":[100],"uncertainty.":[104],"Mahalanobis":[105],"distance":[106],"based":[107],"similar":[108],"day":[109],"weighting":[110],"introduced":[112],"prune":[114],"training":[116],"data.":[117],"The":[118],"numerical":[119],"testing":[120],"results":[121],"illustrate":[122],"that":[123],"proposed":[125],"exhibits":[127],"better":[128],"performance":[129],"comparison":[131],"original":[133],"SBL":[134,138],"model":[135],"weighted":[137],"without":[139],"analysis.":[141]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}