A Method for Identification of Anomalous Geological Zones
| Autor: | A. B. Derendyaev, V. G. Gitis, K. N. Petrov |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
010302 applied physics
Radiation Nonparametric statistics 020206 networking & telecommunications Sample (statistics) 02 engineering and technology Condensed Matter Physics computer.software_genre 01 natural sciences Field (geography) Electronic Optical and Magnetic Materials Identification (information) Simple (abstract algebra) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Classification methods Data mining Electrical and Electronic Engineering computer Preference (economics) Geology |
| Zdroj: | Journal of Communications Technology and Electronics. 65:1531-1541 |
| ISSN: | 1555-6557 1064-2269 |
| DOI: | 10.1134/s1064226920120074 |
| Popis: | In the paper, a new approach to identifying zones with rare anomalous manifestations of geological processes is proposed. The approach is based on two one-class classification methods of machine learning: the method of minimum area of alarm and the method of preference. The algorithm of minimum area of alarm is nonparametric. It is trained on a sample of anomalous events and computes the field of anomalous zones. The knowledge obtained by this method is non-verbalized. The method of preference allows approximating the obtained solution by a rather simple logical rule that defines the anomalous region in terms of analyzed properties of the geological environment. Examples of this approach to finding areas of possible foci of strong earthquakes and to make a regional forecast of deposits are considered. |
| Databáze: | OpenAIRE |
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