On the specific heat capacity estimation of metal oxide-based nanofluid for energy perspective–A comprehensive assessment of data analysis techniques

M Jamei, I Ahmadianfar, IA Olumegbon, A Asadi… - … Communications in Heat …, 2021 - Elsevier
The main aim of the present study is to investigate the capabilities of four robust machine
learning method-the Kernel Extreme Learning Machine (KELM), Adaptive Regression …

Modeling thermal conductivity enhancement of metal and metallic oxide nanofluids using support vector regression

IO Alade, TA Oyehan, IK Popoola, SO Olatunji… - Advanced Powder …, 2018 - Elsevier
Enhancing thermal conductivity of nanofluids is an important objective in heat transfer
applications. Experimental measurement of thermal conductivity is time consuming …

Employing ensemble learning techniques for modeling nanofluids' specific heat capacity

O Deymi, F Hadavimoghaddam, S Atashrouz… - … Communications in Heat …, 2023 - Elsevier
Accurate investigation of nanofluids' specific heat capacity as an effective thermophysical
parameter in applications of heat transfer-based equipment and solar-based systems can …

Exploring the specific heat capacity of water-based hybrid nanofluids for solar energy applications: A comparative evaluation of modern ensemble machine learning …

Z Said, P Sharma, RM Elavarasan, AK Tiwari… - Journal of Energy …, 2022 - Elsevier
The current study aims to give insight into the usefulness of three underutilized yet
exceptionally efficient machine learning approaches in estimating the specific heat capacity …

On the evaluation of thermal conductivity of nanofluids using advanced intelligent models

A Hemmati-Sarapardeh, A Varamesh, MN Amar… - … Communications in Heat …, 2020 - Elsevier
Accurate knowledge of thermal conductivity (TC) of nanofluids is emphasized in studies
related to the thermophysical aspects of nanofluids. In this work, a comprehensive review of …

On the assessment of specific heat capacity of nanofluids for solar energy applications: Application of Gaussian process regression (GPR) approach

M Jamei, I Ahmadianfar, IA Olumegbon… - Journal of Energy …, 2021 - Elsevier
To characterize the performance of nanofluids for heat transfer applications in solar systems,
an accurate estimation of their specific heat capacity (SHC) is of paramount importance. To …

An insight into the prediction of TiO2/water nanofluid viscosity through intelligence schemes

MH Ahmadi, A Baghban, M Ghazvini… - Journal of Thermal …, 2020 - Springer
Viscosity can be mentioned as one of the most crucial properties of nanofluids due to its
ability to describe the fluid resistance to flow, and as the result it affects other phenomena …

Nanofluids thermal conductivity prediction applying a novel hybrid data-driven model validated using Monte Carlo-based sensitivity analysis

A Naseri, M Jamei, I Ahmadianfar… - Engineering with …, 2022 - Springer
Accurate estimation of the thermal conductivity of nanofluids plays a key role in industrial
heat transfer applications. Currently available experimental and empirical relationships can …

Thermal conductivity modeling of nanofluids with ZnO particles by using approaches based on artificial neural network and MARS

A Maleki, M Elahi, MEH Assad, M Alhuyi Nazari… - Journal of Thermal …, 2021 - Springer
Nanofluids are attractive alternatives for the current heat transfer fluids due to their
remarkably higher thermal conductivity which leads to the improved thermal performance …

Data-driven methods for estimating the effective thermal conductivity of nanofluids: A comprehensive review

A Zendehboudi, R Saidur, IM Mahbubul… - International journal of …, 2019 - Elsevier
There is a growing body of work in the field of nanofluids and several investigations have
been conducted on their thermal conductivities. While the experimental works require …