JournalFactors associated with full childhood vaccination coverage among young mothers in Northern Nigeria
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
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- Citations
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
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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}, }
