Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing microencapsulated PCMs

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Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing microencapsulated PCMs

Suspensions containing microencapsulated phase change materials (MPCMs) play a crucial role in thermal energy storage (TES) systems and have applications in building materials, textiles, and cooling systems. This study focuses on accurately predicting the dynamic viscosity, a critical thermophysical...

書誌詳細
出版年:	Scientific Reports
第一著者:	Hai T.; Basem A.; Alizadeh A.; Sharma K.; jasim D.J.; Rajab H.; Ahmed M.; Kassim M.; Singh N.S.S.; Maleki H.
フォーマット:	論文
言語:	English
出版事項:	Nature Research 2024
オンライン･アクセス:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202875990&doi=10.1038%2fs41598-024-71027-9&partnerID=40&md5=09959957b407de6f091c6d755c71f186

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