tengdanwpu

tengdanwpu's Stars

• Eric-Bradford/TS-EMO

  This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).

  Language:MATLAB1007614

• tufts-ml/KCN

  Kriging Convolutional Networks (KCN) in Tensoflow

  Language:Python443317

• zhandawei/Incremental_Kriging_Assisted_Evolutionary_Algorithm

  A fast Kriging-assisted evolutionary algorithm based on incremental learning

  Language:MATLAB33218

• xw00616/DEN-ARMOEA

  # Introduction of DNN-AR-MOEA This repository contains code necessary to reproduce the experiments presented in Evolutionary Optimization of High-DimensionalMulti- and Many-Objective Expensive ProblemsAssisted by a Dropout Neural Network. Gaussian processes are widely used in surrogate-assisted evolutionary optimization of expensive problems. We propose a computationally efficient dropout neural network (EDN) to replace the Gaussian process and a new model management strategy to achieve a good balance between convergence and diversity for assisting evolutionary algorithms to solve high-dimensional multi- and many-objective expensive optimization problems. mainlydue to the ability to provide a confidence level of their outputs,making it possible to adopt principled surrogate managementmethods such as the acquisition function used in Bayesian opti-mization. Unfortunately, Gaussian processes become less practi-cal for high-dimensional multi- and many-objective optimizationas their computational complexity is cubic in the number oftraining samples. # References If you found DNN-AR-MOEA useful, we would be grateful if you cite the following reference: Evolutionary Optimization of High-DimensionalMulti- and Many-Objective Expensive ProblemsAssisted by a Dropout Neural Network (IEEE Transactions on Systems, Man and Cybernetics: Systems).

  Language:MATLAB242011

• wangjz131/H_Kriging

  matlab code achieving Hierarchical Kriging model (a kind of variable fidelity surrogate, which can be regard as an improved version of co-Kriging)

  Language:MATLAB21117

• gsi-lab/MOSKopt

  Simulation-based stochastic black-box optimization under uncertainty using Stochastic Kriging and Monte Carlo simulation

  Language:MATLAB20204

• FuhgJan/AdaptiveMIVor

  MIVor: An innovative adaptive Kriging approach for efficient problem classification.

  Language:MATLAB18115

• nikivanstein/OWCK

  Optimal Weighted Cluster Kriging/Gaussian Process for Python

  Language:Python10303

• salmanahmed91/Gaussian-Process-Regression-Kriging-coKriging-

  Necessary codes for GP

  Language:MATLAB10101

• Azizimj/Robust-Simulation-Optimization-Kriging

  Robust Simulation Optimization Kriging

  Language:MATLAB9201

• Svdvoort/OpenPC

  An open source multi-element generalized polynomial chaos toolbox for matlab

  Language:Matlab9016

• rdwight/vkikriging

  Kriging and Gradient-Enhanced Kriging for the VKI Lecture Series

  Language:Python8102

• LuXuefei/FastKriging

  Language:MATLAB6

• xw00616/T-SAEA

  Language:MATLAB5100

• chua2019/ABTCK

  Augmented Bayesian treed co-kriging

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• thibault-lahire/bayesian-KPLS

  A Bayesian approach of the KPLS (Kriging using Partial Least Squares) method

  Language:Python3203

• travishsu/SAT_matlab

  Surrogate-Assisted Tuning

  Language:MATLAB3200

• xw00616/TC-SAEA

  Language:MATLAB3100

• ocnaar/Kriging

  Scripts for performing Kriging interpolation.

  Language:MATLAB2101

• xw00616/AB-MOEA

  Language:MATLAB2101