{"id":"https://openalex.org/W7204257652","doi":"https://doi.org/10.30598/barekengvol20iss4pp3053-3066","title":"HVAC-COOLING TOWER ENERGY CONSUMPTION PREDICTION IN COMMERCIAL BUILDINGS USING ADVANCED NEURAL NETWORK FRAMEWORKS","display_name":"HVAC-COOLING TOWER ENERGY CONSUMPTION PREDICTION IN COMMERCIAL BUILDINGS USING ADVANCED NEURAL NETWORK FRAMEWORKS","publication_year":2026,"publication_date":"2026-08-24","ids":{"openalex":"https://openalex.org/W7204257652","doi":"https://doi.org/10.30598/barekengvol20iss4pp3053-3066"},"language":"en","primary_location":{"id":"doi:10.30598/barekengvol20iss4pp3053-3066","doi":"https://doi.org/10.30598/barekengvol20iss4pp3053-3066","is_oa":true,"landing_page_url":"https://doi.org/10.30598/barekengvol20iss4pp3053-3066","pdf_url":"https://ojs3.unpatti.ac.id/index.php/barekeng/article/download/22011/13151","source":{"id":"https://openalex.org/S4210230638","display_name":"BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN","issn_l":"1978-7227","issn":["1978-7227","2615-3017"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BAREKENG: Jurnal Ilmu Matematika dan Terapan","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs3.unpatti.ac.id/index.php/barekeng/article/download/22011/13151","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075207877","display_name":"Mrinal Pandey","orcid":"https://orcid.org/0000-0001-8942-3568","observed_orcids":["https://orcid.org/0000-0001-8942-3568"]},"institutions":[{"id":"https://openalex.org/I4405253735","display_name":"Manav Rachna University","ror":"https://ror.org/0117a2k50","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405253735"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mrinal Pandey","raw_affiliation_strings":["Department of Computer Science and Technology, Manav Rachna University, India"],"raw_orcid":"https://orcid.org/0000-0001-8942-3568","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Manav Rachna University, India","institution_ids":["https://openalex.org/I4405253735"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148377227","display_name":"Monika Goyal","orcid":"https://orcid.org/0000-0002-8521-8628","observed_orcids":["https://orcid.org/0000-0002-8521-8628"]},"institutions":[{"id":"https://openalex.org/I4405253735","display_name":"Manav Rachna University","ror":"https://ror.org/0117a2k50","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405253735"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Monika Goyal","raw_affiliation_strings":["Department of Computer Science and Technology, Manav Rachna University, India"],"raw_orcid":"https://orcid.org/0000-0002-8521-8628","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Manav Rachna University, India","institution_ids":["https://openalex.org/I4405253735"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5148354023","display_name":"Mamta Arora","orcid":"https://orcid.org/0000-0003-0616-8827","observed_orcids":["https://orcid.org/0000-0003-0616-8827"]},"institutions":[{"id":"https://openalex.org/I4405253735","display_name":"Manav Rachna University","ror":"https://ror.org/0117a2k50","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405253735"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mamta Arora","raw_affiliation_strings":["Department of Computer Science and Technology, Manav Rachna University, India"],"raw_orcid":"https://orcid.org/0000-0003-0616-8827","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Manav Rachna University, India","institution_ids":["https://openalex.org/I4405253735"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405253735"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.53154297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"4","first_page":"3053","last_page":"3066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9854000210762024,"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":0.9854000210762024,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.007499999832361937,"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/T14098","display_name":"Energy Efficiency in Computing","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/hvac-energy-consumption","display_name":"HVAC energy consumption","score":0.9279999732971191},{"id":"https://openalex.org/keywords/cooling-towers","display_name":"cooling towers","score":0.6510000228881836},{"id":"https://openalex.org/keywords/commercial-buildings","display_name":"commercial buildings","score":0.9210000038146973},{"id":"https://openalex.org/keywords/load-forecasting","display_name":"load forecasting","score":0.8679999709129333},{"id":"https://openalex.org/keywords/gated-recurrent-unit","display_name":"gated recurrent unit","score":0.8349999785423279},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"long short-term memory","score":0.9259999990463257},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.9959999918937683},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.8420000076293945},{"id":"https://openalex.org/keywords/time-series-forecasting","display_name":"time series forecasting","score":0.8610000014305115},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"hyperparameter optimization","score":0.7670000195503235},{"id":"https://openalex.org/keywords/building-energy-efficiency","display_name":"building energy efficiency","score":0.7540000081062317}],"concepts":[{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.7577999830245972},{"id":"https://openalex.org/C122346748","wikidata":"https://www.wikidata.org/wiki/Q1798773","display_name":"HVAC","level":3,"score":0.7483000159263611},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7059000134468079},{"id":"https://openalex.org/C2777831296","wikidata":"https://www.wikidata.org/wiki/Q12518","display_name":"Tower","level":2,"score":0.5867999792098999},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5152999758720398},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5019999742507935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4952999949455261},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.4636000096797943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4429999887943268},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.42250001430511475},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4025000035762787},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4018999934196472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39719998836517334},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.36399999260902405},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.34599998593330383},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30090001225471497},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C2779027077","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Electric energy consumption","level":4,"score":0.27970001101493835},{"id":"https://openalex.org/C3020065929","wikidata":"https://www.wikidata.org/wiki/Q11379","display_name":"Total energy","level":3,"score":0.2766000032424927},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.263700008392334}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.30598/barekengvol20iss4pp3053-3066","doi":"https://doi.org/10.30598/barekengvol20iss4pp3053-3066","is_oa":true,"landing_page_url":"https://doi.org/10.30598/barekengvol20iss4pp3053-3066","pdf_url":"https://ojs3.unpatti.ac.id/index.php/barekeng/article/download/22011/13151","source":{"id":"https://openalex.org/S4210230638","display_name":"BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN","issn_l":"1978-7227","issn":["1978-7227","2615-3017"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BAREKENG: Jurnal Ilmu Matematika dan Terapan","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:090465c0a1564cc595e328ce92fe3b38","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/090465c0a1564cc595e328ce92fe3b38","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Barekeng, Vol 20, Iss 4 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.30598/barekengvol20iss4pp3053-3066","doi":"https://doi.org/10.30598/barekengvol20iss4pp3053-3066","is_oa":true,"landing_page_url":"https://doi.org/10.30598/barekengvol20iss4pp3053-3066","pdf_url":"https://ojs3.unpatti.ac.id/index.php/barekeng/article/download/22011/13151","source":{"id":"https://openalex.org/S4210230638","display_name":"BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN","issn_l":"1978-7227","issn":["1978-7227","2615-3017"],"is_oa":true,"is_in_doaj":true,"is_core":false,"listed_in":["doaj","jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BAREKENG: Jurnal Ilmu Matematika dan Terapan","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9090999960899353,"id":"https://metadata.un.org/sdg/7"},{"display_name":"Climate action","score":0.685699999332428,"id":"https://metadata.un.org/sdg/13"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204257652.pdf","grobid_xml":"https://content.openalex.org/works/W7204257652.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W2000424045","https://openalex.org/W2033239634","https://openalex.org/W2064675550","https://openalex.org/W2128120029","https://openalex.org/W2255466643","https://openalex.org/W2580662672","https://openalex.org/W2605614336","https://openalex.org/W2763500568","https://openalex.org/W2794209590","https://openalex.org/W2803818130","https://openalex.org/W2965791322","https://openalex.org/W2982189404","https://openalex.org/W3024476713","https://openalex.org/W3025055317","https://openalex.org/W3028869275","https://openalex.org/W3043389165","https://openalex.org/W3043685378","https://openalex.org/W3125531171"],"related_works":["https://openalex.org/W4285822433","https://openalex.org/W4386409437","https://openalex.org/W4417434978","https://openalex.org/W4362564544","https://openalex.org/W4411504497","https://openalex.org/W4390549949","https://openalex.org/W7129194000","https://openalex.org/W7214218240","https://openalex.org/W7110522435","https://openalex.org/W4392111128"],"abstract_inverted_index":{"Today,":[0],"a":[1,58,190],"major":[2],"area":[3],"of":[4,10,27,49,64,91,115,137,149,159,162],"concern":[5],"is":[6,29,32,43,189,199],"the":[7,18,23,35,46,52,87,92,108,112,128,147,150,154,160,165,168,177],"huge":[8],"consumption":[9,25,48,90,203],"energy":[11,20,24,50,89,202],"worldwide.":[12],"The":[13,118,184],"modern":[14],"buildings":[15,28],"are":[16,111],"considered":[17],"largest":[19],"consumers.":[21],"When":[22],"pattern":[26],"analyzed,":[30],"attention":[31],"diverted":[33],"towards":[34],"\u201cHeating,":[36],"Ventilation,":[37],"and":[38,78,85,104,132,146,174,181,198],"Air":[39],"Conditioning\u201d":[40],"plant,":[41],"which":[42],"accountable":[44],"for":[45,107,144,176,193,205],"maximum":[47],"in":[51,95,201],"buildings.":[53,97],"This":[54],"research":[55,185],"work":[56],"proposes":[57],"Deep":[59],"learning":[60],"framework":[61],"including":[62],"variants":[63],"Artificial":[65],"Neural":[66,71],"Network":[67,72],"(ANN),":[68],"namely,":[69],"Recurrent":[70,80],"(RNN),":[73],"Long-Short":[74],"Term":[75],"Memory":[76],"(LSTM),":[77],"Gated":[79],"Units":[81],"(GRU)":[82],"to":[83,127],"analyze":[84],"predict":[86],"abnormal":[88],"HVAC":[93,206],"plants":[94],"commercial":[96],"Also,":[98],"proficient":[99],"pre-processing,":[100],"exploratory":[101],"data":[102,196],"analysis,":[103],"hyperparameter":[105],"tuning":[106],"proposed":[109,119],"models":[110,120,136,161],"key":[113],"factors":[114],"this":[116],"research.":[117],"have":[121],"exhibited":[122],"significant":[123],"improvement":[124],"as":[125],"compared":[126],"original":[129],"RNN,":[130],"LSTM,":[131],"GRU":[133,138,163,188],"models.":[134],"Different":[135],"were":[139],"created":[140],"using":[141],"different":[142],"values":[143],"hyperparameters,":[145],"results":[148],"experiments":[151],"performed":[152],"on":[153],"dataset":[155],"show":[156],"that":[157,187],"one":[158],"outperformed":[164],"others":[166],"with":[167],"least":[169],"Mean":[170],"Squared":[171],"Errors":[172],"(0.006)":[173],"(0.005)":[175],"two":[178],"months":[179],"April":[180],"August,":[182],"respectively.":[183],"reveals":[186],"better":[191],"option":[192],"time":[194],"series":[195],"analysis":[197],"useful":[200],"prediction":[204],"plants.":[207]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-08-27T00:00:00"}