Forecasting the productivity of a solar distiller enhanced with an inclined absorber plate using stochastic gradient descent in artificial neural networks

Solar distillers are of significant importance in advanced technologies, as they provide a sustainable approach to address the issue of water purification. The utilization of innovative methodologies holds considerable significance in improving solar distiller performance. For that, this study imple...

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Vydané v:	Multiscale and Multidisciplinary Modeling, Experiments and Design Ročník 7; číslo 3; s. 1819 - 1829
Hlavní autori:	Mohammed, Suha A., Al-Haddad, Luttfi A., Alawee, Wissam H., Dhahad, Hayder A., Jaber, Alaa Abdulhady, Al-Haddad, Sinan A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 01.07.2024
Predmet:	Characterization and Evaluation of Materials Engineering Mathematical Applications in the Physical Sciences Mechanical Engineering Numerical and Computational Physics Original Paper Simulation Solid Mechanics Solar distillers Neural network Stochastic gradient descent Prediction Machine learning
ISSN:	2520-8160, 2520-8179
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