Journal · 2022

Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction

Humphrey Adun, Ifeoluwa Wole-Osho, Eric C. Okonkwo, Tonderai Ruwa, Terfa Agwa, Kenechi Onochie, Henry Ukwu, Olusola Bamisile, Mustafa Dagbasi

Cited by 26 Neural Computing and Applications DOI

Abstract

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Publication details

Venue
Neural Computing and Applications
Type
Journal · 2022
DOI
10.1007/s00521-022-07038-2
Citations
26 · via Crossref, 17 September 2026

Cite this publication

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APA

Adun, H., Wole-Osho, I., Okonkwo, E. C., Ruwa, T., Agwa, T., Onochie, K., Ukwu, H., Bamisile, O., & Dagbasi, M. (2022). Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction. Neural Computing and Applications. https://doi.org/10.1007/s00521-022-07038-2

Harvard

Adun, H., Wole-Osho, I., Okonkwo, E.C., Ruwa, T., Agwa, T., Onochie, K., Ukwu, H., Bamisile, O. and Dagbasi, M. (2022) 'Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction', Neural Computing and Applications. doi: 10.1007/s00521-022-07038-2.

IEEE

H. Adun, I. Wole-Osho, E. C. Okonkwo, T. Ruwa, T. Agwa, K. Onochie, H. Ukwu, O. Bamisile, and M. Dagbasi, "Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction," Neural Computing and Applications, 2022. doi: 10.1007/s00521-022-07038-2.

Vancouver

Adun H, Wole-Osho I, Okonkwo EC, Ruwa T, Agwa T, Onochie K, et al. Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction. Neural Computing and Applications. 2022. doi: 10.1007/s00521-022-07038-2.

MLA

Adun, Humphrey, et al.. "Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction." Neural Computing and Applications, 2022. https://doi.org/10.1007/s00521-022-07038-2.

Chicago

Adun, H., Wole-Osho, I., Okonkwo, E. C., Ruwa, T., Agwa, T., Onochie, K., Ukwu, H., Bamisile, O., Dagbasi, M.. "Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction." Neural Computing and Applications (2022). https://doi.org/10.1007/s00521-022-07038-2.

BibTeX

@article{adun2022, title={Estimation of thermophysical property of hybrid nanofluids for solar Thermal applications: Implementation of novel Optimizable Gaussian Process regression (O-GPR) approach for Viscosity prediction}, author={Adun, Humphrey and Wole-Osho, Ifeoluwa and Okonkwo, Eric C. and Ruwa, Tonderai and Agwa, Terfa and Onochie, Kenechi and Ukwu, Henry and Bamisile, Olusola and Dagbasi, Mustafa}, journal={Neural Computing and Applications}, year={2022}, doi={10.1007/s00521-022-07038-2}, }

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