A Kriging–NARX Model for Uncertainty Quantification of Nonlinear Stochastic Dynamical Systems in Time Domain-Reference-Cited by-同舟云学术

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A Kriging–NARX Model for Uncertainty Quantification of Nonlinear Stochastic Dynamical Systems in Time Domain

Published:2020-07 Issue:7 Volume:146 Page:04020070
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Bhattacharyya Biswarup¹^ORCID,Jacquelin Eric²^ORCID,Brizard Denis³^ORCID

Affiliation:

1. Ph.D. Student, Univ. Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406, Lyon F69622, France (corresponding author). ORCID: .

2. Professor, Univ. Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406, Lyon F69622, France. ORCID: .

3. Researcher, Univ. Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406, Lyon F69622, France. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EM.1943-7889.0001792

Reference56 articles.

1. Computer model validation with functional output

2. A Critical Appraisal of Design of Experiments for Uncertainty Quantification

3. A New Class of Wavelet Networks for Nonlinear System Identification

4. Nonlinear System Identification

5. Identification of MIMO non-linear systems using a forward-regression orthogonal estimator

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