## 3 Results
### FCAZ Recognition of the Strongest Earthquake-Prone Areas
The aforesaid allows interpreting, with a high degree of reliability, the recognized FCAZ zones (Figures 7b and 8) as the areas prone to earthquakes with \(M\geq 7.75\) in the mountain belt of the Andes and on the Pacific Coast of the Kamchatka Peninsula and the Kuril Islands. The recognized zones prone to the strongest earthquakes in Kamchatka and on the Kuril Islands are well aligned with the results of a long-term seismic forecast for IX 2013-VIII 2018, using the method of Academician of RAS [PERSON]. In [53], earthquakes with \(M=5.7\)-7.2 were expected throughout the Pacific Coast of Kamchatka with a varying probability level. That said, during the above-mentioned time interval, earthquakes with \(M\)\(\geq 7.7\) were expected in the coastal zone of the Avacha Bay and near the shores of Southern Kamchatka. Fairly big FCAZ zones are situated in these areas as well (Figure 8a). The best justification for the reliability of recognition results is a pure experiment, i.e., the analysis of the alignment of FCAZ zones and the location of the epicenters of earthquakes (with \(M\geq M_{0}\)) that occurred after the end of the instrumental catalog used for recognition purposes. For instance, three earthquakes with \(M\geq 7.75\) occurred in the mountain belt of the South American Andes after 2013: on 1 April 2014, with \(M=8.2\) (northwest of the Chili coast), on 16 September 2015, with \(M=8.3\) (Chili coast), and on 16 April 2016, with \(M=7.8\) (Ecuador). Information about these strongest earthquakes was not used for recognition purposes in any manner whatsoever. The epicenters of earthquakes of 2014, 2015, and 2016 are shown in Figure 7b using black, purple, and blue stars, respectively. The first two epicenters are located strictly inside the FCAZ zones. The third one is a short distance away from the boundaries of the recognized zones. This allowed obtaining an argument in favor of the reliability of the completed FCAZ recognition, both weighty and independent from research results. Summarizing the results obtained, an important achievement should be noted. For the first time, the strongest earthquake-prone areas were successfully recognized based on the objective classification without involving morphstructural zoning and the formation of learning sets. That said, the results are generally well aligned with those previously obtained independently using the EPA method (for details, see below). Accordingly, it is shown that FCAZ method is applicable to the system observation of regions with a very high seismicity level. FCAZ Recognition of the Areas Prone to Strong and Significant Earthquakes for One and Several Threshold Magnitudes  
The regions with a lower seismicity level than in the previous section of the article: California, the Altai-Sayan region and the Baikal-Transbaikal region, the Caucasus, as well as the Crimean Peninsula, and the northwestern Caucasus are considered. The sets of recognition objects were formed based on the epicenters of crustal earthquakesfrom the following catalogs: ANSS (1960\(-\)2012, California), Earthquakes in the USSR and Earthquakes of Northern Eurasia (1962-2008, the Caucasus; 1962-2008, Crimea and northwestern Caucasus; 1962-2009, the Altai-Sayan region; and 1962-2010, the Baikal-Transbaikal region). Based on the assessment of \(M_{\rm c}\), it was decided to use the epicenters of earthquakes with \(M\geq M_{\rm R}=3.0\) (31,874 epicenters) as recognition objects in California [54; 55; 56]; in the Altai-Sayan region, \(M\geq M_{\rm R}=2.8\) (3647 epicenters) [57]; in the Caucasus, \(M\geq M_{\rm R}=3.0\) (6980 epicenters) [21; 22; 58; 59]; in Crimea and northwestern Caucasus, \(M\geq M_{\rm R}=2.0\) (2398 epicenters) [60; 61]; and in the Baikal-Transbaikal region, \(M\geq M_{\rm R}=2.7\) (11,297 epicenters) [35].