{"id":"https://openalex.org/W2798634422","doi":"https://doi.org/10.1109/smartgridcomm.2017.8340676","title":"Household energy consumption prediction by feature selection of lifestyle data","display_name":"Household energy consumption prediction by feature selection of lifestyle data","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2798634422","doi":"https://doi.org/10.1109/smartgridcomm.2017.8340676","mag":"2798634422"},"language":"en","primary_location":{"id":"doi:10.1109/smartgridcomm.2017.8340676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2017.8340676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Smart Grid Communications (SmartGridComm)","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/A5053698849","display_name":"Kosuke Nishida","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kosuke Nishida","raw_affiliation_strings":["Department of Mathematical Informatics, NTT Corporation"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Informatics, NTT Corporation","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101795095","display_name":"Akiko Takeda","orcid":"https://orcid.org/0000-0002-8846-4496"},"institutions":[{"id":"https://openalex.org/I4210134673","display_name":"The Institute of Statistical Mathematics","ror":"https://ror.org/03jcejr58","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I4210134673","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akiko Takeda","raw_affiliation_strings":["The Institute of Statistical Mathematics, RIKEN Center for Advanced Intelligence Project"],"affiliations":[{"raw_affiliation_string":"The Institute of Statistical Mathematics, RIKEN Center for Advanced Intelligence Project","institution_ids":["https://openalex.org/I4210126580","https://openalex.org/I4210134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040460257","display_name":"Satoru Iwata","orcid":"https://orcid.org/0000-0002-6467-1335"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoru Iwata","raw_affiliation_strings":["Department of Mathematical Informatics, University of Tokyo"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Informatics, University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087990431","display_name":"Mariko Kiho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mariko Kiho","raw_affiliation_strings":["\u00a7R&D Department TEPCO Reserch Institute, Tokyo Electric Power Company Holdings, Inc"],"affiliations":[{"raw_affiliation_string":"\u00a7R&D Department TEPCO Reserch Institute, Tokyo Electric Power Company Holdings, Inc","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015164597","display_name":"Isao Nakayama","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Isao Nakayama","raw_affiliation_strings":["\u00a7R&D Department TEPCO Reserch Institute, Tokyo Electric Power Company Holdings, Inc"],"affiliations":[{"raw_affiliation_string":"\u00a7R&D Department TEPCO Reserch Institute, Tokyo Electric Power Company Holdings, Inc","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5053698849"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2938,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62261389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"235","last_page":"240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9850999712944031,"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":0.9850999712944031,"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":0.9325000047683716,"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/feature-selection","display_name":"Feature selection","score":0.8471469879150391},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6531267166137695},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.6259323358535767},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6223472356796265},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5914642214775085},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5850805640220642},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4944303035736084},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47341281175613403},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.46469518542289734},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.4639793038368225},{"id":"https://openalex.org/keywords/bayesian-multivariate-linear-regression","display_name":"Bayesian multivariate linear regression","score":0.45896482467651367},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45635345578193665},{"id":"https://openalex.org/keywords/predictive-power","display_name":"Predictive power","score":0.45242229104042053},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4471745491027832},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4435860514640808},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.43260475993156433},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.42569828033447266},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4180524945259094},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.41755998134613037},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3825538158416748},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.33892661333084106},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15478724241256714},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13897225260734558},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08021751046180725}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.8471469879150391},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6531267166137695},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.6259323358535767},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6223472356796265},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5914642214775085},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5850805640220642},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4944303035736084},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47341281175613403},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.46469518542289734},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.4639793038368225},{"id":"https://openalex.org/C64946054","wikidata":"https://www.wikidata.org/wiki/Q4874476","display_name":"Bayesian multivariate linear regression","level":3,"score":0.45896482467651367},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45635345578193665},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.45242229104042053},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4471745491027832},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4435860514640808},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.43260475993156433},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.42569828033447266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4180524945259094},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41755998134613037},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3825538158416748},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.33892661333084106},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15478724241256714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13897225260734558},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08021751046180725},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/smartgridcomm.2017.8340676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2017.8340676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Smart Grid Communications (SmartGridComm)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2020607720","https://openalex.org/W2028348615","https://openalex.org/W2064759762","https://openalex.org/W2071258353","https://openalex.org/W2100662401","https://openalex.org/W2121464401","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2148820137","https://openalex.org/W2169747850","https://openalex.org/W2204185640","https://openalex.org/W2342680502","https://openalex.org/W2560679604","https://openalex.org/W2581513538","https://openalex.org/W3141396188","https://openalex.org/W6678176430","https://openalex.org/W6681754992","https://openalex.org/W6684786097","https://openalex.org/W6687749948","https://openalex.org/W6730326506"],"related_works":["https://openalex.org/W2606692828","https://openalex.org/W4309298396","https://openalex.org/W2074089485","https://openalex.org/W2378624038","https://openalex.org/W2140265721","https://openalex.org/W3199622279","https://openalex.org/W3035695858","https://openalex.org/W2349373437","https://openalex.org/W2349542682","https://openalex.org/W2564506044"],"abstract_inverted_index":{"This":[0,52],"study":[1,57],"proposes":[2],"a":[3,26,92],"prediction":[4,76],"model":[5],"for":[6,44,49,61],"the":[7,16,22,31,55,66,74,83],"annual":[8],"power":[9],"consumption":[10,48],"of":[11,21,78,86,91],"general":[12],"households":[13],"based":[14],"on":[15,58],"large-scale":[17],"questionnaire":[18,63],"about":[19],"lifestyle":[20],"household.":[23],"By":[24],"combining":[25],"feature":[27,59],"selection":[28,60],"technique":[29],"with":[30,89],"multivariate":[32],"linear":[33],"regression":[34],"model,":[35],"we":[36,72],"can":[37],"find":[38],"important":[39],"features,":[40],"i.e.,":[41],"key":[42],"questionnaires,":[43],"estimating":[45],"seasonal":[46],"electricity":[47],"ordinary":[50],"households.":[51],"may":[53],"be":[54],"first":[56],"actual":[62],"data":[64],"in":[65],"energy":[67],"field.":[68],"Through":[69],"numerical":[70],"experiments,":[71],"confirmed":[73],"high":[75],"performance":[77],"our":[79,87],"method":[80,88],"by":[81],"comparing":[82],"test":[84],"accuracy":[85],"that":[90],"naive":[93],"one.":[94]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
