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Inicio  /  Applied Sciences  /  Vol: 11 Par: 11 (2021)  /  Artículo
ARTÍCULO
TITULO

Comparison of Six Machine-Learning Methods for Predicting the Tensile Strength (Brazilian) of Evaporitic Rocks

Mohamed Yusuf Hassan and Hasan Arman    

Resumen

Determination of rock tensile strength (TS) is an important task, especially during the initial design stage of engineering applications such as tunneling, slope stability, and foundation. Owing to its simplicity, the Brazilian tensile strength (BTS) test is widely used to assess the TS of rocks indirectly. Powerful regularization techniques such as the Elastic Net, Ridge, and Lasso; and Keras sequential models based on TensorFlow neural networks can be successfully used to predict BTS.

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