Strong Earthquake-Prone Areas Recognition Based on an Algorithm with a Single Pure Training Class I. Altai-Sayan-Baikal Region, М ≥ 6.0

Dzeboev, B.A.; Gvishiani, A.D.; Belov, I.O.; Agayan, S.M.; Tatarinov, V.N.; Barykina, Y.V.

Авторы: Dzeboev B.A., Gvishiani A.D., Belov I.O., Agayan S.M., Tatarinov V.N., Barykina Yu V.
Журнал: Izvestiya. Physics of the Solid Earth
Том: 55
Номер: 4
Год издания: 2019
Издательство: Pleiades Publishing, Inc.
Местоположение издательства: New York, USA
Первая страница: 563
Последняя страница: 575
Оригинальные версии: Распознавание мест возможного возникновения сильных землетрясений на основе алгоритма с единственным чистым классом обучения: I. Алтай-Саяны-Прибайкалье. М ≥ 6.0
DOI: 10.1134/S1069351319040050
Аннотация: A new version of the Barrier algorithm is proposed for recognition of strong-earthquake prone regions based on training over a single reliable training class. The modification of the algorithm consists in creating blocks that reveal the geological–geophysical features (attributes) characteristic of the recognized highly seismic objects and provide their quantitative estimates. The recognition of the areas prone to earthquakes with M ≥ 6.0 is carried out for the Altai–Sayan–Baikal region. The results of the recognition are used for assessing the effect of the remote earthquakes that occurred in the Altai–Sayan orogenic region on the stability of structural-tectonic crustal blocks in the contact zone of the West Siberian platform and the Siberian plate.
Добавил в систему: Гвишиани Алексей Джерменович

	ИСТИНА	Войти в систему Регистрация
	ФНКЦ РР
	Главная Поиск Статистика О проекте Помощь

ИСТИНА

ФНКЦ РР

Strong Earthquake-Prone Areas Recognition Based on an Algorithm with a Single Pure Training Class I. Altai-Sayan-Baikal Region, М ≥ 6.0статья

Прикрепленные файлы