Toward the accurate estimation of elliptical side orifice discharge coefficient applying two rigorous kernel-based data-intelligence paradigms
Abstract In the present study, two kernel-based data-intelligence paradigms, namely, Gaussian Process Regression (GPR) and Kernel Extreme Learning Machine (KELM) along with Generalized Regression Neural Network (GRNN) and Response Surface Methodology (RSM), as the validated schemes, employed to prec...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-99166-3 |