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Published July 16, 2022 | Version v1.0
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Modified adaptive surrogate modeling (MASM)

Authors/Creators

  • 1. Wuhan University
  • 2. University of New Hampshire
  • 3. University of Maryland
  • 4. University of Chinese Academy of Sciences
  • 5. Sun Yat-sen University

Description

We employed adaptive surrogate modeling in this study to establish a fast and practical framework for the iterative optimization of a complex physical model. We slightly improved the Adaptive Surrogate Modeling-based Optimization Parameter Optimization and Distribution Estimation (ASMO-PODE) method proposed by Gong et al. (2017), called the Modified adaptive surrogate modeling (MASM), and applied Bayesian optimization twice to reduce the time cost of Monte Carlo iterations.

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