Development of the Algorithmic Basis of the FCAZ Method for Earthquake-Prone Area Recognition - Sergey M. Agayan; Boris A. Dzeboev; Shamil R. Bogoutdinov; Ivan O. Belov; Boris V. Dzeranov; Dmitriy A. Kamaev (Applied Sciences, 2023)
The present paper continues the series of publications by the authors devoted to solving the problem of recognition regions with potential high seismicity. It is aimed at the development of the mathematical apparatus and the algorithmic base of the FCAZ method, designed for effective recognition of earthquake-prone areas. A detailed description of both the mathematical algorithms included in the FCAZ in its original form and those developed in this paper is given. Using California as an example, it is shown that a significantly developed algorithmic FCAZ base makes it possible to increase the reliability and accuracy of FCAZ recognition. In particular, a number of small zones located at a fairly small distance from each other but having a close “internal” connection are being connected into single large, high-seismicity areas.