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A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification
Joint Authors
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-03-16
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed.
Firstly, quotient function (QF) is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem.
Secondly, the quotient function method (QFM) is proposed to select the optimal regularization parameter based on the quadratic programming theory.
For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are taken into consideration.
Finally, numerical and experimental examples are utilized to validate the performance of the QFM.
Furthermore, the Generalized Cross-Validation (GCV) method and the L-curve method are taken as the comparison methods.
The results indicate that the proposed QFM is adaptive to different measuring points, noise levels, and types of dynamic load.
American Psychological Association (APA)
Gao, Wei& Yu, Kaiping& Wu, Ying. 2016. A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification. Shock and Vibration،Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1119593
Modern Language Association (MLA)
Gao, Wei…[et al.]. A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification. Shock and Vibration No. 2016 (2016), pp.1-16.
https://search.emarefa.net/detail/BIM-1119593
American Medical Association (AMA)
Gao, Wei& Yu, Kaiping& Wu, Ying. A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification. Shock and Vibration. 2016. Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1119593
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1119593