Parameter Determination Method of Soil Constitutive Model Based on Machine Learning

In order to better determine the model parameters and improve the safety and stability of construction, an optimized identification method of constitutive model parameters with improved RCGA is proposed by combining the current optimization theory. The experimental results indicate that the improved...

Full description

Saved in:
Bibliographic Details
Published in:Wireless communications and mobile computing 2022, Vol.2022, p.1-10
Main Authors: Song, Zhibin, Liu, Shurong, Jiang, Mingyue, Yao, Suling
Format: Article
Language:English
Subjects:
Algebra
Algorithms
Constitutive models
Engineering
Genetic algorithms
Identification methods
Machine learning
Mathematical models
Mutation
Optimization
Parameter identification
Population
Tournaments & championships
Variables
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In order to better determine the model parameters and improve the safety and stability of construction, an optimized identification method of constitutive model parameters with improved RCGA is proposed by combining the current optimization theory. The experimental results indicate that the improved RCGA algorithm proposed in the study has stronger recognition capabilities and optimization effects than the traditional NSGA-II algorithm and determine the parameters of the constitutive model more accurately. Moreover, it is found that the parameters obtained by the proposed improved algorithm have validity and accuracy, when parameter P0′=50 kPa, comparing the obtained optimal parameters with the real laboratory clay parameters.
ISSN:1530-8669
1530-8677
DOI:10.1155/2022/3765169