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A Nonlinear Method for Component Separation of Dam Effect Quantities Using Kernel Partial Least Squares and Pseudosamples

Auteur(s):




Médium: article de revue
Langue(s): en 
Publié dans: Advances in Civil Engineering, , v. 2019
Page(s): 1-12
DOI: 10.1155/2019/1958173
Abstrait:

Existing component separation methods fail to consider the complex nonlinear relationship between dam effect quantities and environmental variables. In this study, a novel nonlinear component separation method for the effect quantities is proposed by combining kernel partial least squares (KPLS) and pseudosamples. By this method, a nonlinear monitoring model is established based on KPLS, and the complicated nonlinear relationship between the effect quantities and environmental variables can be determined accurately through the model. Furthermore, special pseudosamples are constructed to separate independent components and coupling influence components of environmental factors from the KPLS model. These methods have been applied into a super-high arch dam, and the separated displacement components conform to the general deformation law. The presented results indicate that it is more reliable than traditional multiple linear regression models.

Copyright: © 2019 Wenzhong Yin et al. et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

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    sur cette fiche
  • Reference-ID
    10403261
  • Publié(e) le:
    28.12.2019
  • Modifié(e) le:
    28.12.2019