Published April 3, 2025
| Version v1
Model
Open
ANN model presented in "Estimation of pile stiffness in non-homogeneous soils through Artificial Neural Networks"
Authors/Creators
-
1.
Universidad de Las Palmas de Gran Canaria
Description
This repository contains the best of the models developed in the scientific article "Estimation of pile stiffness in non-homogeneous soils through Artificial Neural Networks" by Román Quevedo-Reina, Guillermo M. Álamo, Juan J. Aznárez. (https://doi.org/10.1016/j.engstruct.2024.117999)
This is an enssemble model of 20 artificial neural networks with 7 neurons in the input layer, 3 hidden layers with 145 neurons per hidden layer, and 4 neuron in the output layer.
Notes
Included in this upload are the following files:
APP-VERSION of the surrogate model.
- Soil_Impedance_Calculation_Model_Instaler: executable for installing the app (MATLAB Runtime is downloaded and installed automatically). Matlab license is not required.
- Soil_Impedance_Calculation_Model: file for installing the app inside Matlab. Matlab license is required with "Statistics and Machine Learning" and "Deep Learning" Toolboxes.
CODE-VERSION of the surrogate model. Matlab license required with "Statistics and Machine Learning" and "Deep Learning" Toolboxes.
- class_model_pile: Matlab class that defines the surrogate model
- model_monopile: developed surrogate model
- User_manual: document explaining the use of these files
Files
User_manual.pdf
Files
(13.3 MB)
Additional details
Related works
- Is described by
- Journal article: 10.1016/j.engstruct.2024.117999 (DOI)
Funding
- Agencia Estatal de Investigación
- Design of offshore wind turbine supports including advanced models of dynamic soil-structure interaction and seismic action using neural nets (PID2020-120102RB-I00) MCIN/ AEI/ 10.13039/501100011033
- Ministerio de Universidades
- FPU research fellowship (FPU19/04170)