SoftwareApplication
identifier: 10.4121/21257199
name: Code supporting the paper: High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations
description: Code supporting the paper: High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations
description: This online resource shows three archived folders: Matlab, Python, and App that contain relevant code and data for the article: High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations. Within the Matlab folder, one finds the codes used for the generation of the large dataset. Here, the file Main.m is the main file and from there, one can run the Monte Carlo simulation. Within the Python folder, one finds the codes used for training the neural networks and creating the online application. The file Data.mat contains the data generated by the Matlab Monte Carlo simulation. The files run_bound.py, run_rsa.py, and run_tse.py train the neural networks, of which the best scoring ones are saved in the folder Training. The DashApp folder contains the code for the creation of the Application. Within the App folder, one finds the executable nn_R2_app.exe that one can run, once the archived folder is unzipped. When running the app, it opens in a browser. This was checked in Windows.
author: https://orcid.org/0000-0003-3601-6496
author: https://orcid.org/0000-0003-2212-1711
author: https://orcid.org/0000-0003-3461-8848
keywords: Machine learning
keywords: Post-burn contraction
keywords: Feedforward neural network
keywords: Monte Carlo simulations
keywords: Online application
license:
  creative work: creativeWork
    name: EUPL-1.2
reference publication: fams.2023.1098242

https://orcid.org/0000-0003-3601-6496
type: Person
given name: Ginger
family name: Egberts
name: Ginger Egberts

https://orcid.org/0000-0003-2212-1711
type: Person
given name: Fred
family name: Vermolen
name: Fred Vermolen

https://orcid.org/0000-0003-3461-8848
type: Person
given name: Paul van
family name: Zuijlen
name: Paul van Zuijlen

fams.2023.1098242
type: ScholarlyArticle
name: High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations
url: https://doi.org/10.3389%2Ffams.2023.1098242