OpenCossan is an open and free toolbox for uncertainty quantification and management.

Fast nonlinear FEA tailored for topology optimization

OpenCossan represents the core of COSSAN software. All the algorithms and methods have been coded in a matlab toolbox allowing numerical analysis, reliability analysis, simulation, sensitivity, optimization, robust design and much more. Released under the LGPL license, the engine can be used, modified and redistributed free of charge. It is supp…

MATLAB implementations of the simplex method, dual simplex method and sensitivity analysis.

SoBioS is an easy-to-run Matlab code to compute Sobol' indices for biological systems.

Sensitivity analysis using simulation decomposition

Codes for parameter estimation and sensitivity analysis of QSP models for colon cancer. This is a part of the National Cancer Institute funded project titled "Data-driven QSP software for personalized colon cancer treatment" Achyuth Manoj, Susanth Kakarla, Suvra Pal and Souvik Roy.

This suite is an ensemble of codes developed to conduct a global sensitivity analysis on an multimodal energy harvesting system with periodic excitation.

MatLab scripts for performing a sensitivity analysis of LSTM networks for fall detection wearable sensors based on the SisFall dataset

A sensitivity toolbox that is tailored to the design process in the presence of uncertainties

Code for the paper "Stochastic analysis of the electromagnetic induction effect on a neuron's action potential dynamics"

Integral equation method for Topology Optimization

Computes a sensitivity analysis for different objective functions for a 2D linear elasticity problem with standard finite elements

Master Thesis 2021

The New Morris Method was proposed by Campolongo and Braddock [Reliab. Engng Syst. Saf. 64 (1999) 1] as an extension of the Morris Method [Technometrics 33 (1991) 161] to include estimation of two-factor interaction effects.

Files used for the Cibernetica Fisiologica project. I've used the Matlab sensitivity toolbox to find the parameters that make the model fits the data simulated.

Modeling sensitivity analysis techniques using MATLAB