Amin-Eshghi / A-polynomial-regression-machine-learning-approach-for-reliability-based-optimizationLinks
This is a compact code for reliability analysis under uncertainty using a Polynomial Regression Machine Learning approach. The code implements a stochastic response surface method (SRSM) which quantifies the uncertainty in a performance function for the purpose of reliability-based design optimization (RBDO).
☆13Updated 5 years ago
Alternatives and similar repositories for A-polynomial-regression-machine-learning-approach-for-reliability-based-optimization
Users that are interested in A-polynomial-regression-machine-learning-approach-for-reliability-based-optimization are comparing it to the libraries listed below
Sorting:
- This Matlab files are used to demonstrate on how to perform Reliability-based Design Optimization (RBDO) using FERUM. Two approaches are …☆13Updated last year
- time-variant reliability analysis method☆14Updated 5 years ago
- an active-learning method for reliability analysis based on multi-fidelity kriging model☆37Updated last year
- Gradient-enhanced Kriging surrogate model☆21Updated 2 months ago
- Source codes for Probability-Adaptive Kriging in n-Ball (PAK-Bn) (Kim & Song, 2020)☆10Updated 2 months ago
- Customized FERUM (Finite Element Reliability Using Matlab)☆13Updated 3 years ago
- MIVor: An innovative adaptive Kriging approach for efficient problem classification.☆18Updated 5 years ago
- ☆16Updated 3 months ago
- The code is used to solve structural reliability analysis problem via the BSC_RLCB method☆14Updated 3 years ago
- In his project, we proposed a new acquisition function for kriging-based reliability analysis, namely expected uncertainty reduction (EUR…☆11Updated 3 years ago
- Simple Bayesian optimization in MATLAB, with interface to interact with simulations in ANSYS.☆18Updated 2 years ago
- Source code of the paper: Dang C., Xu, J. Unified reliability assessment for problems with low- to high-dimensional random inputs using t…☆10Updated 3 years ago
- Reliability-based Design Optimization☆9Updated last year
- A MATLAB implementation of the co-kriging process using the DACE toolbox☆38Updated 8 years ago
- Representative point selection by the GF-discrepancy minimization technique for the probability density evolution method (PDEM).☆13Updated 7 months ago
- Bayesian Framework for Updating☆13Updated 2 years ago
- Matlab codes for Arbitrary Polynomial Chaos Expansion☆12Updated 5 years ago
- matlab code achieving Hierarchical Kriging model (a kind of variable fidelity surrogate, which can be regard as an improved version of co…☆23Updated 6 years ago
- Multi-fidelity probability machine learning☆18Updated 5 months ago
- ☆17Updated 4 years ago
- A Matlab toolbox for stochastic response analysis by DR-PDEE/GE-GDEE☆25Updated last year
- A Matlab toolbox for solving the generalized density evolution equation (GDEE) in the probability density evolution method (PDEM) by fini…☆27Updated 7 months ago
- Kriging for Analysis, Design optimization, And expLoration (KADAL)☆19Updated 3 years ago
- Subset simulation is a method of estimating low probability events. Here I adapt SS to perform well with correlated inputs.☆10Updated 6 years ago
- The code is for two phase demonstration as example 1 shown in the paper - Gao, Yi, and Yongming Liu. "Reliability-based topology optimiza…☆11Updated 3 years ago
- Surrogate Based Design Optimization Toolbox☆31Updated 6 years ago
- The STK is a (not so) Small Toolbox for Kriging. Its primary focus is on the interpolation/regression technique known as kriging, which i…☆41Updated 7 months ago
- multi-fidelity neural network☆19Updated last year
- Tools to construct surrogate models based on Hermitian polynomial bases. Includes full-factorial and sparse polynomial chaos expansions v…☆10Updated 6 years ago
- MSherri-eng / Bayesian-Finite-Element-Model-Updating-Using-Evolutionary-Markov-Chain-Monte-Carlo-algorithms☆11Updated 4 years ago