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AN ADAPTIVE MULTIFIDELITY PC-BASED ENSEMBLE KALMAN INVERSION FOR INVERSE PROBLEMS

文献类型：期刊论文

作者Yan, Liang2; Zhou, Tao1
刊名INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
出版日期2019
卷号9期号:3页码:205-220
关键词Bayesian inverse problems ensemble Kalman inversion multifidelity polynomial chaos surrogate modeling
ISSN号2152-5080
DOI10.1615/Int.J.UncertaintyQuantification.2019029059
英文摘要The ensemble Kalman inversion (EKI), as a derivative-free methodology, has been widely used in the parameter estimation of inverse problems. Unfortunately, its cost may become moderately large for systems described by high-dimensional nonlinear PDEs, as EKI requires a relatively large ensemble size to guarantee its performance. In this paper, we propose an adaptive multifidelity polynomial chaos (PC) based EKI technique to address this challenge. Our new strategy combines a large number of low-order PC surrogate model evaluations and a small number of high-fidelity forward model evaluations, yielding a multifidelity approach. Specifically, we present a new approach that adaptively constructs and refines a local multifidelity PC surrogate during the EKI simulation. Since the forward model evaluations are only required for updating the low-order local multifidelity PC model, whose number can be much smaller than the total ensemble size of the classic EKI, the entire computational costs are thus significantly reduced. The new algorithm was tested through the two-dimensional time fractional inverse diffuision problems and demonstrated great effectiveness in comparison with PC-based EKI and classic EKI.
资助项目NSF of China[11822111] ; NSF of China[11688101] ; NSF of China[91630203] ; NSF of China[11571351] ; NSF of China[11731006] ; NSF of China[11771081] ; Qing Lan project of Jiangsu Province ; Southeast University's Zhishan Young Scholars Program ; Science Challenge Project[TZ2018001] ; National Key Basic Research Program[2018YFB0704304] ; NCMIS ; Youth Innovation Promotion Association (CAS)
WOS研究方向Engineering ; Mathematics
语种英语
WOS记录号WOS:000478800200002
出版者BEGELL HOUSE INC
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/35243]  
专题计算数学与科学工程计算研究所
通讯作者Zhou, Tao
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, LSEC, Inst Computat Math & Sci Engn Comp, Beijing 100190, Peoples R China
2.Southeast Univ, Dept Math, Nanjing 210096, Jiangsu, Peoples R China
推荐引用方式
GB/T 7714		 Yan, Liang,Zhou, Tao. AN ADAPTIVE MULTIFIDELITY PC-BASED ENSEMBLE KALMAN INVERSION FOR INVERSE PROBLEMS[J]. INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION,2019,9(3):205-220.
APA Yan, Liang,&Zhou, Tao.(2019).AN ADAPTIVE MULTIFIDELITY PC-BASED ENSEMBLE KALMAN INVERSION FOR INVERSE PROBLEMS.INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION,9(3),205-220.
MLA Yan, Liang,et al."AN ADAPTIVE MULTIFIDELITY PC-BASED ENSEMBLE KALMAN INVERSION FOR INVERSE PROBLEMS".INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION 9.3(2019):205-220.

入库方式： OAI收割

来源：数学与系统科学研究院

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