Evaluation of Creep Behavior of Soft Soils by Utilizing Multisensor Data Combined with Machine Learning

Evaluation of Creep Behavior of Soft Soils by Utilizing Multisensor Data Combined with Machine Learning

To identify the unknown values of the parameters of Burger’s constitutive law, commonly used for the evaluation of the creep behavior of the soft soils, this paper demonstrates a procedure relying on the data obtained from multiple sensors, where each sensor is used to its best advantage. The geophy...

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Bibliographic Details
Main Authors: Bačić, M. (Author), Gavin, K. (Author), Kovačević, M.S (Author), Librić, L. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Antennas
Burger’s model
Creep
Creep behaviors
Creep parameters
Learning algorithms
Machine learning
Multi-sensor data
neural network
Neural-networks
Nondestructive examination
nondestructive testing
Parameter estimation
particle swarm optimization
Particle swarm optimization (PSO)
remote sensing
Remote sensing
Remote-sensing
S models
soft soil creep
Soft soil creep
Soft soils
Soil creep
Soil testing
Soils
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