用于大规模参数估计问题的自适应多输出高斯过程代用模型

IF 1.5 4区 工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Xiaolong Lyu, Dan Huang, Liwei Wu, Ding Chen
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引用次数: 0

摘要

目的复杂工程结构中的参数估计通常需要使用仿真模型进行重复计算,从而导致大量计算成本。本文旨在介绍一种自适应多输出高斯过程(MOGP)代理模型,用于耗时模型的参数估计。设计/方法/途径建立 MOGP 代理模型是为了在估算过程中取代计算成本高昂的有限元法(FEM)分析。受传统预期改进(EI)方法的启发,我们提出了一种新颖的 MOGP 自适应采样方法,旨在减少建立代用模型所需的采样点数量。通过两个数学实例和一个混凝土拱坝的回溯分析应用测试,证明了所提方法的有效性。提出的自适应采样方法与 MOGP 代理模型相结合,在涉及评估成本高昂的模型的参数估计问题中,尤其是那些具有高维输出的参数估计问题中,显示出明显的优势。这种基于传统 EI 方法的改进型自适应采样方法更适合多输出问题,因此在众多实际工程应用中具有很高的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An adaptive multi-output Gaussian process surrogate model for large-scale parameter estimation problems

Purpose

Parameter estimation in complex engineering structures typically necessitates repeated calculations using simulation models, leading to significant computational costs. This paper aims to introduce an adaptive multi-output Gaussian process (MOGP) surrogate model for parameter estimation in time-consuming models.

Design/methodology/approach

The MOGP surrogate model is established to replace the computationally expensive finite element method (FEM) analysis during the estimation process. We propose a novel adaptive sampling method for MOGP inspired by the traditional expected improvement (EI) method, aiming to reduce the number of required sample points for building the surrogate model. Two mathematical examples and an application in the back analysis of a concrete arch dam are tested to demonstrate the effectiveness of the proposed method.

Findings

The numerical results show that the proposed method requires a relatively small number of sample points to achieve accurate estimates. The proposed adaptive sampling method combined with the MOGP surrogate model shows an obvious advantage in parameter estimation problems involving expensive-to-evaluate models, particularly those with high-dimensional output.

Originality/value

A novel adaptive sampling method for establishing the MOGP surrogate model is proposed to accelerate the procedure of solving large-scale parameter estimation problems. This modified adaptive sampling method, based on the traditional EI method, is better suited for multi-output problems, making it highly valuable for numerous practical engineering applications.

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来源期刊
Engineering Computations
Engineering Computations 工程技术-工程:综合
CiteScore
3.40
自引率
6.20%
发文量
61
审稿时长
5 months
期刊介绍: The journal presents its readers with broad coverage across all branches of engineering and science of the latest development and application of new solution algorithms, innovative numerical methods and/or solution techniques directed at the utilization of computational methods in engineering analysis, engineering design and practice. For more information visit: http://www.emeraldgrouppublishing.com/ec.htm
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