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Application of the kernel method to the inverse geosounding problem.

Authors
  • Hidalgo, Hugo
  • Sosa León, Sonia
  • Gómez-Treviño, Enrique
Type
Published Article
Journal
Neural Networks
Publisher
Elsevier
Publication Date
Jan 01, 2003
Volume
16
Issue
3-4
Pages
349–353
Identifiers
PMID: 12672430
Source
Medline
License
Unknown

Abstract

Determining the layered structure of the earth demands the solution of a variety of inverse problems; in the case of electromagnetic soundings at low induction numbers, the problem is linear, for the measurements may be represented as a linear functional of the electrical conductivity distribution. In this paper, an application of the support vector (SV) regression technique to the inversion of electromagnetic data is presented. We take advantage of the regularizing properties of the SV learning algorithm and use it as a modeling technique with synthetic and field data. The SV method presents better recovery of synthetic models than Tikhonov's regularization. As the SV formulation is solved in the space of the data, which has a small dimension in this application, a smaller problem than that considered with Tikhonov's regularization is produced. For field data, the SV formulation develops models similar to those obtained via linear programming techniques, but with the added characteristic of robustness.

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