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Prediction of the Void Ratio Parameter in Mineral Tailings Using Gene Expression Programming

Auteur(s):


Médium: article de revue
Langue(s): en 
Publié dans: Advances in Civil Engineering, , v. 2020
Page(s): 1-12
DOI: 10.1155/2020/8838104
Abstrait:

Mineral tailing deposits are one of the most important issues in the field of geotechnical engineering. The void ratio of mineral tailings is an essential parameter for investigating the geotechnical behavior of tailings. However, there has not yet been a comprehensive empirical formulation for initial prediction of the void ratio of mineral tailings. In this study, the void ratio of various types of mineral waste is estimated by using gene expression programming (GEP). Therefore, taking into consideration the effective physical parameters that affect the estimation of this parameter, eight different models are presented. A reliable experimental database collected from different sources in the literature was applied to develop the GEP models. The performance of the developed GEP models was measured based on coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE). According to the results, the model with effective stress (σ'), initial void ratio (e0), and parameters of R² = 0.92, MAE = 0.109, and RMSE = 0.180 performed the best. Finally, a new empirical formulation for the initial prediction of the void ratio parameter is proposed based on the aforementioned analyses.

Copyright: © Ali Akbar Heshmati R. et al. et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

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  • Reference-ID
    10446719
  • Publié(e) le:
    19.10.2020
  • Modifié(e) le:
    19.10.2020