ReLU-activated deep learning approach for simulating and sensitivity of casson hybrid nanofluid dynamics with radiative effects.
- DOI
- 10.1016/j.apradiso.2026.112843
- Published
- 2026 Nov
- Container
- Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
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- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.apradiso.2026.112843,
title = {ReLU-activated deep learning approach for simulating and sensitivity of casson hybrid nanofluid dynamics with radiative effects.},
author = {Li S and Talha M and Shah Z and Magdich A and Zayani HM},
year = {2026},
journal = {Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine},
doi = {10.1016/j.apradiso.2026.112843},
url = {https://doi.org/10.1016/j.apradiso.2026.112843}
}RIS
TY - JOUR TI - ReLU-activated deep learning approach for simulating and sensitivity of casson hybrid nanofluid dynamics with radiative effects. AU - Li S AU - Talha M AU - Shah Z AU - Magdich A AU - Zayani HM PY - 2026 JO - Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine DO - 10.1016/j.apradiso.2026.112843 UR - https://doi.org/10.1016/j.apradiso.2026.112843 ER -
APA
S, L., M, T., Z, S., A, M., & HM, Z. (2026). ReLU-activated deep learning approach for simulating and sensitivity of casson hybrid nanofluid dynamics with radiative effects.. Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine. https://doi.org/10.1016/j.apradiso.2026.112843
Source records
- pubmed · retrieved 2026-09-26T02:43:00.605Z