{"id":"https://openalex.org/W2984104210","doi":"https://doi.org/10.1109/iisa.2019.8900731","title":"Data Mining for Smart Cities: Predicting Electricity Consumption by Classification","display_name":"Data Mining for Smart Cities: Predicting Electricity Consumption by Classification","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2984104210","doi":"https://doi.org/10.1109/iisa.2019.8900731","mag":"2984104210"},"language":"en","primary_location":{"id":"doi:10.1109/iisa.2019.8900731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa.2019.8900731","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5038228806","display_name":"Konstantinos Christantonis","orcid":null},"institutions":[{"id":"https://openalex.org/I183898223","display_name":"International Hellenic University","ror":"https://ror.org/00708jp83","country_code":"GR","type":"education","lineage":["https://openalex.org/I183898223"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Konstantinos Christantonis","raw_affiliation_strings":["International Hellenic University,The Data Mining and Analytics Research Group School of Science & Technology,Thessaloniki,Greece","The Data Mining and Analytics Research Group School of Science & Technology, International Hellenic University, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Hellenic University,The Data Mining and Analytics Research Group School of Science & Technology,Thessaloniki,Greece","institution_ids":["https://openalex.org/I183898223"]},{"raw_affiliation_string":"The Data Mining and Analytics Research Group School of Science & Technology, International Hellenic University, Thessaloniki, Greece","institution_ids":["https://openalex.org/I183898223"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071901091","display_name":"Christos Tjortjis","orcid":"https://orcid.org/0000-0001-8263-9024"},"institutions":[{"id":"https://openalex.org/I183898223","display_name":"International Hellenic University","ror":"https://ror.org/00708jp83","country_code":"GR","type":"education","lineage":["https://openalex.org/I183898223"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Christos Tjortjis","raw_affiliation_strings":["International Hellenic University,The Data Mining and Analytics Research Group School of Science & Technology,Thessaloniki,Greece","The Data Mining and Analytics Research Group School of Science & Technology, International Hellenic University, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Hellenic University,The Data Mining and Analytics Research Group School of Science & Technology,Thessaloniki,Greece","institution_ids":["https://openalex.org/I183898223"]},{"raw_affiliation_string":"The Data Mining and Analytics Research Group School of Science & Technology, International Hellenic University, Thessaloniki, Greece","institution_ids":["https://openalex.org/I183898223"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183898223"],"apc_list":null,"apc_paid":null,"fwci":3.9824,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.95061678,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9998999834060669,"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":0.9998999834060669,"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/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9933000206947327,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9923999905586243,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6762214303016663},{"id":"https://openalex.org/keywords/electricity","display_name":"Electricity","score":0.6274502277374268},{"id":"https://openalex.org/keywords/predictive-power","display_name":"Predictive power","score":0.6101245880126953},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.5355648398399353},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.5086916089057922},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.5035616755485535},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4873448312282562},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43449482321739197},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43034279346466064},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.42865189909935},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26592087745666504},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.21639099717140198},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18353432416915894},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.16391542553901672},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09055444598197937}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6762214303016663},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.6274502277374268},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.6101245880126953},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5355648398399353},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.5086916089057922},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.5035616755485535},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4873448312282562},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43449482321739197},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43034279346466064},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.42865189909935},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26592087745666504},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.21639099717140198},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18353432416915894},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.16391542553901672},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09055444598197937},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iisa.2019.8900731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa.2019.8900731","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1664361434","https://openalex.org/W1990785420","https://openalex.org/W1996663009","https://openalex.org/W2013539530","https://openalex.org/W2029784539","https://openalex.org/W2033592659","https://openalex.org/W2038619526","https://openalex.org/W2040585915","https://openalex.org/W2053843348","https://openalex.org/W2057160778","https://openalex.org/W2060193958","https://openalex.org/W2075621955","https://openalex.org/W2091693228","https://openalex.org/W2103226621","https://openalex.org/W2104950272","https://openalex.org/W2126831543","https://openalex.org/W2166651278","https://openalex.org/W2167152259","https://openalex.org/W2170112669","https://openalex.org/W2474694100","https://openalex.org/W2782672556","https://openalex.org/W2782707924","https://openalex.org/W3150435615"],"related_works":["https://openalex.org/W3189884647","https://openalex.org/W2884834684","https://openalex.org/W2917165927","https://openalex.org/W4385950391","https://openalex.org/W3123614577","https://openalex.org/W3023917431","https://openalex.org/W4311802502","https://openalex.org/W4379911910","https://openalex.org/W1998320186","https://openalex.org/W3192139338"],"abstract_inverted_index":{"Data":[0],"analysis":[1,108],"can":[2],"be":[3],"applied":[4],"to":[5,58],"power":[6],"consumption":[7,43,102],"data":[8,35,55,127],"for":[9,13,111,128],"predictions":[10],"that":[11,137],"allow":[12],"the":[14,26,99,120,123,138,143],"efficient":[15],"scheduling":[16],"and":[17,28,53,61,72,82,97,119],"operation":[18],"of":[19,30,101,125,140,145],"electricity":[20,42],"generation.":[21],"This":[22],"work":[23],"focuses":[24],"on":[25,36],"parameterization":[27],"evaluation":[29],"predictive":[31,63],"algorithms":[32,71],"utilizing":[33],"metered":[34],"predefined":[37],"time":[38,114],"intervals.":[39],"More":[40],"specifically,":[41],"as":[44,49,80],"a":[45,117],"total,":[46],"but":[47],"also":[48,135],"main":[50],"usages/spaces":[51],"breakdown":[52],"weather":[54,77,126],"are":[56,74,84],"used":[57],"develop,":[59],"train":[60],"test":[62],"models.":[64],"A":[65],"technical":[66],"comparison":[67],"between":[68],"different":[69,113],"classification":[70],"methodologies":[73],"provided.":[75],"Several":[76],"metrics,":[78],"such":[79],"temperature":[81],"humidity":[83],"exploited,":[85],"along":[86],"with":[87],"explanatory":[88],"past":[89],"consuming":[90],"variables.":[91],"The":[92,107,133],"target":[93],"variable":[94],"is":[95,109],"binary":[96],"expresses":[98],"volume":[100],"regarding":[103],"each":[104],"individual":[105],"residence.":[106],"conducted":[110],"two":[112],"intervals":[115],"during":[116],"day,":[118],"outcomes":[121],"showcase":[122],"necessity":[124],"predicting":[129],"residential":[130],"electrical":[131],"consumption.":[132],"results":[134],"indicate":[136],"size":[139],"dwellings":[141],"affects":[142],"accuracy":[144],"model.":[146]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}