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Measurement Techniques

Erschienen in:

05.07.2017 | GENERAL PROBLEMS OF METROLOGY AND MEASUREMENT TECHNIQUE

Modeling, Reproduction, and Mapping of Geofields with and Without Measurement Noise. Part 3. Integral Equation, Radial Grid, and Soft Computing Methods

verfasst von: A. M. Pashayev, R. A. Sadykhov, S. B. Habibullayev

Erschienen in: Measurement Techniques | Ausgabe 2/2017

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Abstract

The effectiveness of boundary integral equation and grid-free methods for radial grids, as well as solutions of classical and nonclassical modeling and recovery problems for geological fields are analyzed. It is shown that, as opposed to the methods employing a variational technique and radial basis neural networks, hybrid algorithms (fuzzy neural networks, genetic algorithms, and Kalman filter) for solving identification and recovery problems are more stable with respect to noise and give positive results even with conflicting data and significant measurement noise.

Vorheriger Artikel Metrological Capabilities of the National Primary Standard for the Units of Relative Humidity of Gases, Molar (Volume) Fraction of Moisture, and Temperature of the Dew/Frost Point, GET 151-2014

Nächster Artikel Method for Certification Monitoring of Surface Inhomogeneities of Optics Based on Frequency Analysis of the Surface Profile

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Titel: Modeling, Reproduction, and Mapping of Geofields with and Without Measurement Noise. Part 3. Integral Equation, Radial Grid, and Soft Computing Methods
verfasst von: A. M. Pashayev
R. A. Sadykhov
S. B. Habibullayev
Publikationsdatum: 05.07.2017
Verlag: Springer US
Erschienen in: Measurement Techniques / Ausgabe 2/2017
Print ISSN: 0543-1972
Elektronische ISSN: 1573-8906
DOI: https://doi.org/10.1007/s11018-017-1159-6

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