Application of Fuzzy Logic in Seismic Zonation
Faculty of Computing, Health and Science
School of Computer and Information Science
Traditional statistical methods for seismic zonation require information from many subjects, such as regional geology and neotectonics, seismicity, stress field, damage analysis of historic earthquakes, geophysics and others. These subjects are weighted differently during statistics. In fact, the information from most of these subjects is more like fuzzy sets, ie, it is a sort of estimation rather than precise data. In this paper we propose a fuzzy logic system that uses crustal structural features (seismotectonics) and historic seismic activities (seismicity) as two fuzzy inputs for seismic zonation. Seismotectonics is a combination of features from regional and deep geology, neotectonics, stress field and geophysics whereas seismicity is defined by historic earthquakes and their damages to some specific areas. Applying this fuzzy system to the northeastern Tibetan Plateau, a well-known intraplate seismic region in the world, outlines are not only the existing well recognised seismic zones where large earthquakes took place in history, but also some areas where there have been no strong shocks occurred for the last 2000 years. The traditional statistical methods are not able to evaluate such areas due to the lack of the historic seismicity information.