训练Kriging 替代模型: sm=KRG(theta0=[1e-2])sm.set_training_values(inputs_train,outputs_train)sm.train()# 显示为:___________________________________________________________________________Kriging_________________________
使用pyKriging pyKriging的目的旨在简化代理模型的创建过程。下列例子演示了如何创建抽样计划、在这些位置评估测试函数、创建和训练一个Kriging模型、并且添加点来减少模型的均方根误差。 import pyKriging from pyKriging.krige import kriging from pyKriging.samplingplan import samplingplan # The Kriging model starts...
If you’d prefer to do your surrogate modeling in Python, some of the same technology is implemented onpyKriging.com. As the name suggests, this is a Python implementation of the surrogate modeling technique called Kriging. The code also allows you to iteratively improve the accuracy of your ...
KrigingPythonSoftwareIn this contribution, a detailed description of a Python based application tool that enables fast implementation of the Self-Optimizing Control (SOC) technology with the help of surrogate models is presented. The paper also outlines the potential uses of the Metacontrol (from ...
Multi-Fidelity Kriging 介绍:美国密歇根大学(University of Michigan)变复杂度Kriging模型。 Emukit 介绍:一个很好用的Python工具包,用于在不确定性环境下(Uncertainty)进行仿真建模及决策。包括:变复杂度仿真、贝叶斯优化(Bayesian optimisation)、实验设计(Experimental design)、主动学习(Active learning)、敏感性分析(Sen...
Krige用类似的方法用于金矿分布的估计,他用已开采的少数矿点对金矿分布进行建模,后来这类方法被称为Kriging或高斯过程回归(Gaussian process regression, GPR)。本文将介绍基于高斯过程的贝叶斯优化,其他类型的贝叶斯优化算法将在文末作简要总结。此外,本文关于GPR的数学原理部分参考了MIT出版的 [Gaussian Processes for ...
Krige用类似的方法用于金矿分布的估计,他用已开采的少数矿点对金矿分布进行建模,后来这类方法被称为Kriging或高斯过程回归(Gaussian process regression, GPR)。本文将介绍基于高斯过程的贝叶斯优化,其他类型的贝叶斯优化算法将在文末作简要总结。此外,本文关于GPR的数学原理部分参考了MIT出版的 [Gaussian Processes for ...