{"id":"https://openalex.org/W1570620328","doi":"https://doi.org/10.1109/icit.2015.7125313","title":"Improvement of MLP models for forecasting electrical energy consumption using OBD and OBS methods","display_name":"Improvement of MLP models for forecasting electrical energy consumption using OBD and OBS methods","publication_year":2015,"publication_date":"2015-03-01","ids":{"openalex":"https://openalex.org/W1570620328","doi":"https://doi.org/10.1109/icit.2015.7125313","mag":"1570620328"},"language":"en","primary_location":{"id":"doi:10.1109/icit.2015.7125313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit.2015.7125313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Industrial Technology (ICIT)","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/A5020570496","display_name":"Jaros\u0142aw Protasiewicz","orcid":"https://orcid.org/0000-0002-9204-921X"},"institutions":[{"id":"https://openalex.org/I4210143086","display_name":"Taipei Institute of Pathology","ror":"https://ror.org/045syea95","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210143086"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Jaroslaw Protasiewicz","raw_affiliation_strings":["Graduate Institute of Computer and Communication Engineering, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Graduate Institute of Computer and Communication Engineering, Taipei, Taiwan","institution_ids":["https://openalex.org/I4210143086"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090385920","display_name":"Jakub S. Sowinski","orcid":null},"institutions":[{"id":"https://openalex.org/I4210129264","display_name":"Inventec (Taiwan)","ror":"https://ror.org/03r46a684","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210129264"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jakub S. Sowinski","raw_affiliation_strings":["Department of Engineering, Inventec Appliances Corporation, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, Inventec Appliances Corporation, Taipei, Taiwan","institution_ids":["https://openalex.org/I4210129264"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5020570496"],"corresponding_institution_ids":["https://openalex.org/I4210143086"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02911946,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1526","last_page":"1531"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9991999864578247,"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":0.9991999864578247,"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/T10320","display_name":"Neural Networks and Applications","score":0.9976000189781189,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9891999959945679,"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/computer-science","display_name":"Computer science","score":0.7102843523025513},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.7076555490493774},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6623216271400452},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6329233646392822},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.600701093673706},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5720395445823669},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4906805753707886},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.44015973806381226},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.42301034927368164},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.41590791940689087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4091850519180298},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.35223859548568726},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34637653827667236},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13706722855567932},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08537757396697998}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7102843523025513},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.7076555490493774},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6623216271400452},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6329233646392822},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.600701093673706},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5720395445823669},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4906805753707886},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.44015973806381226},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.42301034927368164},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.41590791940689087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4091850519180298},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.35223859548568726},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34637653827667236},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13706722855567932},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08537757396697998},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icit.2015.7125313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit.2015.7125313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W8173372","https://openalex.org/W905787346","https://openalex.org/W981034629","https://openalex.org/W1983175601","https://openalex.org/W2019207321","https://openalex.org/W2114766824","https://openalex.org/W2125389748","https://openalex.org/W2130159119","https://openalex.org/W2151767444","https://openalex.org/W2156150815","https://openalex.org/W2313953460","https://openalex.org/W4247523314","https://openalex.org/W6624190021","https://openalex.org/W6677103964","https://openalex.org/W6678583879"],"related_works":["https://openalex.org/W1997864015","https://openalex.org/W2532234348","https://openalex.org/W108084911","https://openalex.org/W2363394879","https://openalex.org/W2349491863","https://openalex.org/W2352593301","https://openalex.org/W4386420510","https://openalex.org/W2361441833","https://openalex.org/W3136869357","https://openalex.org/W3200447293"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,104,133],"apply":[4],"two":[5],"reduction":[6],"algorithms":[7,110],"of":[8,20,65,76,90,101,118,124],"a":[9,21],"neural":[10],"network":[11,24,126],"architecture":[12],"in":[13],"order":[14],"to":[15,142],"improve":[16,114],"the":[17,35,49,59,71,85,115,125,129],"prediction":[18,54,116,146],"quality":[19,117],"multilayer":[22],"perceptron":[23],"(MLP).":[25],"The":[26],"first":[27,72],"algorithm":[28],"is":[29,37,73,87],"Optimal":[30,38],"Brain":[31,39],"Damage":[32],"(OBD),":[33],"whereas":[34],"second":[36,86],"Surgeon":[40],"(OBS).":[41],"Our":[42],"assumptions":[43],"have":[44,67,105],"been":[45,68],"verified":[46],"experimentally":[47],"on":[48],"models":[50],"for":[51,79,93],"electricity":[52,77,91],"consumption":[53,78,92],"using":[55],"real":[56],"data":[57],"from":[58],"Polish":[60],"electroenergetic":[61],"system.":[62],"Two":[63],"series":[64,145],"tests":[66],"carried":[69],"out:":[70],"hourly":[74],"forecast":[75,89],"twenty":[80],"four":[81],"hours":[82],"ahead,":[83],"and":[84,112],"daily":[88],"one":[94],"day":[95],"ahead.":[96],"Taking":[97],"into":[98],"account":[99],"results":[100],"performed":[102],"computations,":[103],"found":[106],"out":[107],"that":[108,136],"both":[109],"OBD":[111],"OBS":[113],"an":[119],"MLP":[120],"network.":[121],"Moreover,":[122],"simplification":[123],"speeds":[127],"up":[128],"training":[130],"process.":[131],"Presumably,":[132],"can":[134,139],"assume":[135],"these":[137],"conclusions":[138],"be":[140],"expanded":[141],"other":[143],"time":[144],"tasks.":[147]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}