排序方式： 共有13条查询结果，搜索用时 15 毫秒
1.
Shebalin P. N. Gvishiani A. D. Dzeboev B. A. Skorkina A. A. 《Doklady Earth Sciences》2022,507(1):930-935
Doklady Earth Sciences - For the first time, a numerical comparison of the General Seismic Zoning (GSZ) maps with the effect of earthquakes that actually occurred after the publication of the maps... 相似文献
2.
A. D. Gvishiani B. A. Dzeboev N. A. Sergeyeva A. I. Rybkina 《Izvestiya Physics of the Solid Earth》2017,53(3):353-365
With the use of the modified version of the original algorithmic Formalized Clustering and Zoning (FCAZ) system, the areas prone to the probable emergence of the epicenters of significant earthquakes are recognized in the joint region of the Crimea and western part of the Northern Caucasus. The selection of this region is justified by the tectonic structure and the presence of the active junction zone of the meganticlinoria. The reliability of the obtained recognition is substantiated by the comparative analysis of the actual and random FCAZ-recognition. For the first time, the problem of recognizing the locations of the probable emergence of the earthquakes' epicenters is solved for two different magnitude thresholds. This allows us to interpret the areas prone to the probable emergence of the epicenters of significant earthquakes as fuzzy sets. 相似文献
3.
Dzeboev B. A. Gvishiani A. D. Belov I. O. Agayan S. M. Tatarinov V. N. Barykina Yu. V. 《Izvestiya Physics of the Solid Earth》2019,55(4):563-575
Izvestiya, Physics of the Solid Earth - A new version of the Barrier algorithm is proposed for recognition of strong-earthquake prone regions based on training over a single reliable training... 相似文献
4.
B. A. Dzeboev 《Doklady Earth Sciences》2017,473(1):338-341
Preliminary work on the creation of a method for monitoring of seismic activity, on the basis of discrete mathematical analysis for further seismic hazard assessment of a territory, is presented. The method developed is tested for the territory of California and adjacent areas of the United States. The results obtained are analyzed for the period of 1980–2015. The nonrandomness of the results is shown by means of an error chart. 相似文献
5.
Clustering the epicenters of Caucasian earthquakes with magnitudes M ≥ 3.0 is carried out, and the epicentral zones of the probable earthquakes with M ≥ 5.0 areas where epicenters of earthquakes with M ≤ 5.0 may occur are recognized by the Fuzzy Clustering and Zoning (FCAZ) algorithmic system developed by the authors at the Geophysical Center of the Russian Academy of Sciences. These zones correspond well to the locations of the epicenters of earthquakes with M ≥ 5.0. The zones recognized in this study are compared with the zones previously recognized by A.D. Gvishiani et al. in 1988 by the Earthquake-Prone Areas Recognition (EPA) technique. The comparison shows that the zones identified by FCAZ are mainly located inside the EPA-zones. The FCAZ-zones are also compared with the zones previously recognized using gravimetric and geological data. The results obtained by different methods closely agree. Contrary to EPA technique FCAZ algorithmic system relies on the DPS algorithm of objective classification that requires only the information about epicenters of the earthquakes in the region under study. 相似文献
6.
Doklady Earth Sciences - This paper shows that the number of aftershocks with a relative magnitude does not depend on the magnitude of the main shock, and, in global and regional consideration, it... 相似文献
7.
This article presents a new Barrier recognition algorithm with learning, designed for recognition of earthquake-prone areas. In comparison to the Crust (Kora) algorithm, used by the classical EPA approach, the Barrier algorithm proceeds with learning just on one “pure” high-seismic class. The new algorithm operates in the space of absolute values of the geological–geophysical parameters of the objects. The algorithm is used for recognition of earthquake-prone areas with М ≥ 6.0 in the Caucasus region. Comparative analysis of the Crust and Barrier algorithms justifies their productive coherence. 相似文献
8.
Gvishiani A. D. Tatarinov V. N. Kaftan V. I. Manevich A. I. Dzeboev B. A. Losev I. V. 《Doklady Earth Sciences》2020,493(1):544-547
Doklady Earth Sciences - The paper presents the results of GNSS observations, provided by the authors in 2010-2019 years, in the zone of contact of tectonic structures of the Siberian platform,... 相似文献
9.
Gvishiani A. D. Dzeboev B. A. Belov I. O. Sergeeva N. A. Vavilin E. V. 《Doklady Earth Sciences》2017,477(2):1488-1493
Doklady Earth Sciences - This report continues a series of works by the authors on earthquake-prone areas recognition by the algorithmic system FCAZ. For the first time, successive earthquake-prone... 相似文献
10.
The fuzzy clustering and zoning method (FCAZm) of systems analysis is suggested for recognizing the areas of the probable generation of the epicenters of significant, strong, and the strongest earthquakes. FCAZm is a modified version of the previous FCAZ algorithmic system, which is advanced by the creation of the blocks of artificial intelligence that develop the system-forming algorithms. FCAZm has been applied for recognizing areas where the epicenters of the strongest (M ≥ 73/4) earthquakes within the Andes mountain belt in the South America and significant earthquakes (M ≥ 5) in the Caucasus can emerge. The reliability of the obtained results was assessed by the seismic-history type control experiments. The recognized highly seismic zones were compared with the ones previously recognized by the EPA method and by the initial version of the FCAZ system. The modified FCAZm system enabled us to pass from simple pattern recognition in the problem of recognizing the locations of the probable emergence of strong earthquakes to systems analysis. In particular, using FCAZm we managed to uniquely recognize a subsystem of highly seismically active zones from the nonempty complement using the exact boundary. 相似文献