Artificial neural network hyperparameters optimization for predicting the thermal conductivity of MXene/graphene nanofluids

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Artificial neural network hyperparameters optimization for predicting the thermal conductivity of MXene/graphene nanofluids

Background: The critical role of thermal conductivity (TC) as a significant thermo-physical property in MXene/graphene-based nanofluids for photovoltaic/thermal systems has motivated recent research into developing precision predictive models. The multilayer perceptron neural network (MLPNN) has eme...

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Bibliographic Details
Published in:	Journal of the Taiwan Institute of Chemical Engineers
Main Author:	Shang Y.; Hammoodi K.A.; Alizadeh A.; Sharma K.; jasim D.J.; Rajab H.; Ahmed M.; Kassim M.; Maleki H.; Salahshour S.
Format:	Article
Language:	English
Published:	Taiwan Institute of Chemical Engineers 2024
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200416163&doi=10.1016%2fj.jtice.2024.105673&partnerID=40&md5=817ca67518d51e0a5b1f9519b0d46ccb

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