IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4939-2323-6_3.html
   My bibliography  Save this book chapter

Multiobjective Inversion and Regularization

In: Model Calibration and Parameter Estimation

Author

Listed:
  • Ne-Zheng Sun

    (University of California at Los Angeles, Department of Civil and Environmental Engineering)

  • Alexander Sun

    (University of Texas at Austin, Bureau of Economic Geology, Jackson School of Geosciences)

Abstract

After incorporating prior information, the inverse problem becomes a bi-criterion optimization problem. The use of prior information in such a way can be seen as a special case of the regularization method introduced in this chapter. Regularization provides a generalframework for increasing the stability of inverse solutions at the priceof possible loss of accuracy. EWR models are often multistatemodels characterized by a set of coupled equations. The statevariable of one equation may depend on states or parameters inother equations. This implies that measurements of one statevariable may provide information for identifying the states and/orparameters in other equations. The inversion of a multistate model iscalled a coupled inverse problem and can be solved by multiobjectiveoptimization (MOO). Various algorithms for solving MOO, includingrecently developed multiobjective evolutionary algorithms, areintroduced. These algorithms can also be used to solvemultiobjective inverse problems.

Suggested Citation

  • Ne-Zheng Sun & Alexander Sun, 2015. "Multiobjective Inversion and Regularization," Springer Books, in: Model Calibration and Parameter Estimation, edition 127, chapter 3, pages 69-105, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4939-2323-6_3
    DOI: 10.1007/978-1-4939-2323-6_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:sprchp:978-1-4939-2323-6_3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.