Random forest regression on pullout resistance of a pile.

Autor: Alsamia, Shaymaa, Koch, Edina
Předmět:
Zdroj: Pollack Periodica; Dec2024, Vol. 19 Issue 3, p28-33, 6p
Abstrakt: This research aims to study the pullout resistance of a helical pile using three methods of machine learning techniques, which are: random forest regression, support vector regression, and adaptive neuro-fuzzy inference system, based on experimental results of a helical pile. The performance of these three techniques has been d compared and the results show that random forest algorithm has best performance than neuro-fuzzy inference system and support vector technique. The results show that machine learning considered a good tool in terms of estimating the pullout resistance of helical piles in the soil. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index