Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
An evolutionary computational approach for formulation of compression index of fine-grained soils
This study presents a robust evolutionary computational technique, called multi-expression programming (MEP), to derive a highly nonlinear model for the prediction of compression index of fine-grained soils. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. The experimental database used for developing the models was established upon 108 consolidation tests conducted on different soils sampled from different construction sites in Iran. The generalization capability of the model was verified via several statistical criteria. The parametric and sensitivity analyses were performed and discussed. The results indicate that the MEP approach accurately characterizes the soil compression index leading to a very good prediction performance. The correlation coefficients between the experimental and predicted soil compression index values are equal to 0.935 and 0.901 for the calibration and testing data sets, respectively. The developed model has a significantly better performance than the existing empirical equations for the soil compression index.
An evolutionary computational approach for formulation of compression index of fine-grained soils
This study presents a robust evolutionary computational technique, called multi-expression programming (MEP), to derive a highly nonlinear model for the prediction of compression index of fine-grained soils. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. The experimental database used for developing the models was established upon 108 consolidation tests conducted on different soils sampled from different construction sites in Iran. The generalization capability of the model was verified via several statistical criteria. The parametric and sensitivity analyses were performed and discussed. The results indicate that the MEP approach accurately characterizes the soil compression index leading to a very good prediction performance. The correlation coefficients between the experimental and predicted soil compression index values are equal to 0.935 and 0.901 for the calibration and testing data sets, respectively. The developed model has a significantly better performance than the existing empirical equations for the soil compression index.
An evolutionary computational approach for formulation of compression index of fine-grained soils
Mohammadzadeh S., Danial (Autor:in) / Bolouri Bazaz, Jafar (Autor:in) / Alavi, Amir H. (Autor:in)
Engineering Applications of Artificial Intelligence ; 33 ; 58-68
2014
11 Seiten, 87 Quellen
Aufsatz (Zeitschrift)
Englisch
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