Simulation of soil stress in earth dams using artificial intelligence models and determination of effective features

Document Type : Research Article


1 PhD candidate, Department of Science and Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

2 Tabriz University

3 29th Boulevard University Sq

4 Associate Professor, Water Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran


The general purpose of this paper is to select effective features and model soil stress in earth dams during construction. Five features, including fill level, duration of construction, reservoir level (impoundment), impounding rate and fill rate, were selected as hybrid model inputs. By performing hybrid algorithm and sensitivity analysis and feature selection method, fill level and duration of construction were recognized as the most effective features in modeling the total stress in selected cells, because concurrent mean square error values for the fill level and duration of construction in TPC25.1, TPC25.3 and TPC25.4 cells were 1.523, 2.747 and 0.750, respectively. In TPC25.2 cell, three features including fill level, duration of construction and impoundment level, had the greatest effect in modeling the total soil stress based on the mean square error value of 5.245. Comparison of the results of the ANN model with ANFIS and GEP showed that although the difference in the accuracy of the models is very small, all three models had acceptable results in the test step, the ANFIS model results indicated that the statistical error measures of , RMSE, MAE and NS in TPC25.4 cell were 0.9955, 0.0227, 0.0185 and 0.9666, respectively. It showed that how much the input data are more scattered, the ANFIS model had more capability than ANN and GEP models to simulate the soil stress in the studied earth dam.


Main Subjects

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