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Brine Evaporation Rate Prediction Methods by Yassine Alami Tahiri is a document available to read on EtoBox.

This study compares the predictive abilities of response surface methodology (RSM) and artificial neural networks (ANN) for estimating brine evaporation rates, considering multiple environmental factors. Results indicate that the ANN model outperforms the RSM model in terms of accuracy and stability, with lower root mean square error and higher coefficient of determination. The research aims to provide a reliable empirical model for predicting brine evaporation, essential for the management of salt lake res

Author

Yassine Alami Tahiri

Language

EN