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Efficacy of historical context and exogenous features on deep learning for cooling load forecasting in chilled water plants.

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Title: Efficacy of historical context and exogenous features on deep learning for cooling load forecasting in chilled water plants.
Authors: Ulfath RE; School of Engineering, RMIT University, Melbourne, Australia. rubaiath.e.ulfath@rmit.edu.au., Cheng CT; School of Engineering, RMIT University, Melbourne, Australia., Pang TY; School of Engineering, RMIT University, Melbourne, Australia., Stewart I; Exergenics, Melbourne, Australia.
Source: Scientific reports [Sci Rep] 2026 Jul 01. Date of Electronic Publication: 2026 Jul 01.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: <searchLink fieldCode="AU" term="%22Ulfath+RE%22">Ulfath RE</searchLink>; School of Engineering, RMIT University, Melbourne, Australia. rubaiath.e.ulfath@rmit.edu.au.<br /><searchLink fieldCode="AU" term="%22Cheng+CT%22">Cheng CT</searchLink>; School of Engineering, RMIT University, Melbourne, Australia.<br /><searchLink fieldCode="AU" term="%22Pang+TY%22">Pang TY</searchLink>; School of Engineering, RMIT University, Melbourne, Australia.<br /><searchLink fieldCode="AU" term="%22Stewart+I%22">Stewart I</searchLink>; Exergenics, Melbourne, Australia.
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        Value: 10.1038/s41598-026-59706-1
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        Text: English
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      – TitleFull: Efficacy of historical context and exogenous features on deep learning for cooling load forecasting in chilled water plants.
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            NameFull: Ulfath RE
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            NameFull: Cheng CT
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            – D: 01
              M: 07
              Text: 2026 Jul 01
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              Y: 2026
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