IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v264y2025ipas0951832025004776.html
   My bibliography  Save this article

Surrogate modeling with functional nonlinear autoregressive models (F-NARX)

Author

Listed:
  • Schär, Styfen
  • Marelli, Stefano
  • Sudret, Bruno

Abstract

We propose a novel functional approach to surrogate modeling of dynamical systems with exogenous inputs. This approach, named Functional Nonlinear AutoRegressive with eXogenous inputs (F-NARX), approximates the system response based on temporal features of the exogenous inputs and the system response. This marks a major step away from the discrete-time-centric approach of classical NARX models, which determines the relationship between selected time steps of the input/output time series. By modeling the system in a time-feature space, F-NARX takes advantage of the temporal smoothness of the process being modeled, providing more stable predictions and reducing the dependence of model performance on the discretization of the time axis.

Suggested Citation

  • Schär, Styfen & Marelli, Stefano & Sudret, Bruno, 2025. "Surrogate modeling with functional nonlinear autoregressive models (F-NARX)," Reliability Engineering and System Safety, Elsevier, vol. 264(PA).
    • Handle: RePEc:eee:reensy:v:264:y:2025:i:pa:s0951832025004776
    DOI: 10.1016/j.ress.2025.111276
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832025004776
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2025.111276?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:264:y:2025:i:pa:s0951832025004776. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.