{"id":"https://openalex.org/W2775370286","doi":"https://doi.org/10.1109/mlsp.2017.8168112","title":"Identification of a thermal building model by learning the dynamics of the solar flux","display_name":"Identification of a thermal building model by learning the dynamics of the solar flux","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2775370286","doi":"https://doi.org/10.1109/mlsp.2017.8168112","mag":"2775370286"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2017.8168112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2017.8168112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"preprint","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/A5052313903","display_name":"Tahar Nabil","orcid":null},"institutions":[{"id":"https://openalex.org/I4210154078","display_name":"Territoires, Villes, Environnement & Soci\u00e9t\u00e9","ror":"https://ror.org/04kwqat20","country_code":"FR","type":"facility","lineage":["https://openalex.org/I117841876","https://openalex.org/I1294671590","https://openalex.org/I2279609970","https://openalex.org/I2802487185","https://openalex.org/I4210087131","https://openalex.org/I4210089394","https://openalex.org/I4210139971","https://openalex.org/I4210154078"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I4210145102","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Tahar Nabil","raw_affiliation_strings":["EDF R&D, TREE, E36, Lab Les Renardi\u00e9res, Ecuelles, France","LTCI, Universit\u00e9 Paris-Saclay, Paris, France"],"affiliations":[{"raw_affiliation_string":"EDF R&D, TREE, E36, Lab Les Renardi\u00e9res, Ecuelles, France","institution_ids":["https://openalex.org/I4210154078"]},{"raw_affiliation_string":"LTCI, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210165912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073675112","display_name":"Fran\u00e7ois Roueff","orcid":"https://orcid.org/0000-0003-2372-0724"},"institutions":[{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I4210145102","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Francois Roueff","raw_affiliation_strings":["LTCI, Universit\u00e9 Paris-Saclay, Paris, France"],"affiliations":[{"raw_affiliation_string":"LTCI, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210165912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016805529","display_name":"Jean-Marc Jicquel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210154078","display_name":"Territoires, Villes, Environnement & Soci\u00e9t\u00e9","ror":"https://ror.org/04kwqat20","country_code":"FR","type":"facility","lineage":["https://openalex.org/I117841876","https://openalex.org/I1294671590","https://openalex.org/I2279609970","https://openalex.org/I2802487185","https://openalex.org/I4210087131","https://openalex.org/I4210089394","https://openalex.org/I4210139971","https://openalex.org/I4210154078"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Marc Jicquel","raw_affiliation_strings":["EDF R&D, TREE, E36, Lab Les Renardi\u00e9res, Ecuelles, France"],"affiliations":[{"raw_affiliation_string":"EDF R&D, TREE, E36, Lab Les Renardi\u00e9res, Ecuelles, France","institution_ids":["https://openalex.org/I4210154078"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011293298","display_name":"Alexandre Girard","orcid":"https://orcid.org/0000-0001-5938-6305"},"institutions":[{"id":"https://openalex.org/I4210096782","display_name":"Laboratoire Pluridisciplinaire de Recherche en Ing\u00e9nierie des Syst\u00e8mes, M\u00e9canique et Energ\u00e9tique","ror":"https://ror.org/00sbth994","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12449238","https://openalex.org/I4210096782","https://openalex.org/I4210143826"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Alexandre Girard","raw_affiliation_strings":["EDF R&D, PRISME, P12, 6 quai Watier, Chatou, France"],"affiliations":[{"raw_affiliation_string":"EDF R&D, PRISME, P12, 6 quai Watier, Chatou, France","institution_ids":["https://openalex.org/I4210096782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5052313903"],"corresponding_institution_ids":["https://openalex.org/I4210154078","https://openalex.org/I4210165912","https://openalex.org/I277688954"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2138931,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9972000122070312,"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"}},"topics":[{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9972000122070312,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9564999938011169,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9556999802589417,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/gaussian","display_name":"Gaussian","score":0.5417478680610657},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.510420024394989},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.48647353053092957},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4753396511077881},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.46163296699523926},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.4382014572620392},{"id":"https://openalex.org/keywords/flux","display_name":"Flux (metallurgy)","score":0.4101654887199402},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3602527379989624},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3360569477081299},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.3216766119003296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31249886751174927},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.25458642840385437},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.23908501863479614},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22741839289665222},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.09265479445457458},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.0897161066532135}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5417478680610657},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.510420024394989},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.48647353053092957},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4753396511077881},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.46163296699523926},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.4382014572620392},{"id":"https://openalex.org/C68709404","wikidata":"https://www.wikidata.org/wiki/Q1134475","display_name":"Flux (metallurgy)","level":2,"score":0.4101654887199402},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3602527379989624},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3360569477081299},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.3216766119003296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31249886751174927},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25458642840385437},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.23908501863479614},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22741839289665222},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.09265479445457458},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0897161066532135},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2017.8168112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2017.8168112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5899999737739563,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W170647656","https://openalex.org/W1486307680","https://openalex.org/W1963718895","https://openalex.org/W1967235646","https://openalex.org/W2040640105","https://openalex.org/W2051389656","https://openalex.org/W2051635872","https://openalex.org/W2052076015","https://openalex.org/W2055936398","https://openalex.org/W2061373768","https://openalex.org/W2064860826","https://openalex.org/W2131871670","https://openalex.org/W2148061324","https://openalex.org/W2149247444","https://openalex.org/W2163121678","https://openalex.org/W2627041774","https://openalex.org/W6739613358"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W2383807498","https://openalex.org/W1997992934","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W2125114371","https://openalex.org/W2019977573","https://openalex.org/W2149980199","https://openalex.org/W3125766170","https://openalex.org/W2040641410"],"abstract_inverted_index":{"This":[0],"article":[1],"deals":[2],"with":[3,85,118,156],"the":[4,17,28,31,49,55,71,81,89,100,106,110,153,164,171,175,181,185,189,193],"identification":[5],"of":[6,30,70,99,105,174,184],"a":[7,20,42,62,76,134,145],"dynamic":[8],"building":[9,136],"model":[10,79,130,137],"from":[11],"on-site":[12],"input-output":[13],"records.":[14],"In":[15],"practice,":[16],"solar":[18,72,176],"gains,":[19],"key":[21],"input,":[22],"are":[23,116,168],"often":[24],"unobserved":[25],"due":[26],"to":[27,37,48,133,162,178],"cost":[29],"associated":[32],"sensor.":[33],"We":[34,74,151,167],"suggest":[35],"here":[36],"replace":[38],"this":[39,59,129],"sensor":[40,60,65],"by":[41,94],"cheap":[43],"outdoor":[44,82],"temperature":[45,56,83],"sensor,":[46],"exposed":[47],"sun.":[50],"Our":[51],"assumption":[52],"is":[53,66,131],"that":[54],"bias":[57],"between":[58],"and":[61,109,192],"second":[63],"sheltered":[64],"an":[67,119,140],"indirect":[68,172],"observation":[69,173],"flux.":[73],"derive":[75],"novel":[77],"state-space":[78,149],"for":[80,93],"bias,":[84],"sudden":[86],"changes":[87],"in":[88,160,187],"weather":[90],"conditions":[91],"accounted":[92],"occasional":[95],"high":[96,107],"variance":[97],"increments":[98],"hidden":[101],"state.":[102],"The":[103],"magnitude":[104],"values":[108],"times":[111],"at":[112],"which":[113],"they":[114],"occur":[115],"estimated":[117],"\u2113":[120],"<sub":[121],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[122],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[123],"-regularized":[124],"maximum":[125],"likelihood":[126],"approach.":[127],"Finally,":[128],"appended":[132],"thermal":[135,165],"based":[138],"on":[139],"equivalent":[141],"RC":[142],"network,":[143],"forming":[144],"conditionally":[146],"linear":[147],"Gaussian":[148],"system.":[150],"apply":[152],"Expectation-Maximization":[154],"algorithm":[155],"Rao-Blackwellised":[157],"particle":[158],"smoothing":[159],"order":[161],"learn":[163],"model.":[166],"able,":[169],"despite":[170],"flux,":[177],"correctly":[179],"estimate":[180],"physical":[182],"parameters":[183],"building,":[186],"particular":[188],"static":[190],"coefficients":[191],"fast":[194],"time":[195],"constant.":[196]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}