A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. The idea is then to develop a surrogate model g which approximates f by training on previous data collected from evaluations of f.

Features

  • Sample selection
  • Construction of the surrogate model
  • Surrogate optimization
  • Sampling can be done through QuasiMonteCarlo.jl
  • Second Order Polynomial
  • Gradient Enhanced Kriging

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License

MIT License

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Additional Project Details

Programming Language

Julia

Related Categories

Julia Data Visualization Software

Registered

2023-11-14