| Autor: |
Goudjil, Kamel, Sbartai, Badreddine |
| Předmět: |
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| Zdroj: |
International Review of Mechanical Engineering; 2017, Vol. 11 Issue 3, p175-180, 6p |
| Abstrakt: |
Several studies applied heuristic methods such as neuronal networks (ANN), genetic algorithms (GA) and particle swarm optimization (PSO) to predict and optimize soil parameters. Therefore, the aim of the present paper is to optimize shear wave velocity of soil. In this direction, the genetic algorithm NSGA II was used to find the optimum values of shear wave velocity of soil that give an actual value of 0.3m settlement post-liquefaction. The results show that our genetic algorithm has been successfully employed to optimize the shear wave velocity (vs) with acceptable test errors oj (R2= 0.9999, RMSE=4.029). Moreover, this algorithm can be easily used for prediction and optimization of other geotechnical systems. The genetic algorithm can solve other problems in this field than the presented in this study. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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