Fuzzy logic-based attenuation relationships of strong motion earthquake records

The objective of this paper is to present new attenuation relationships for free-field peak ground accelerations (PGA) using a fuzzy methodology approach. The used database was compiled from recent earthquakes in Taiwan and USA with magnitudes 5 or greater; and recorded on three different site conditions classified as rock, soil and soft soil. Uncertainty is a condition associated with essentially all aspects of earthquake related science and engineering. The main sources of uncertainty in the estimation of ground motion lie in the characterization of site geology, calculation of closest distances, determination of seismic shaking properties, and in the geotechnical properties of earthquake motion monitoring sites. However, fuzzy logic and statistical analysis can be used to quantify the uncertainties associated with these fundamental features. Fuzzy sets are developed as fuzzy model inputs by dividing the local geologic conditions into three groups as rock, soil and soft soil; epicentral distances into three groups as near, intermediate and far, whereas the output is the horizontal components of peak ground accelerations (PGA). The prediction model is tested with an independent data set for its successful prediction capability. The combination of fuzzy sets to describe natural language and statistics to quantify uncertainties inherent in earthquake ground motion lead to a rational analytical tool. This approach can be used to assess the potential variability in parameters that influence the earthquake intensity.