Integrated evaluation of sand liqufaction based on generalized regression neural network

This paper adopts standard method and Seed method separately to make liquefaction evaluation about saturated sands, based on large drill data in Xiamen. Then, using generalized regression neural network, taking the data that show different evaluated results as training samples and also test samples, we carry out the second evaluation of the remained drill data. The results show that the generalized regression neural network presents a good function and a high forecast precision. In addition, this integrated evaluation method can improve the precision of sand liquefaction of saturated sands, and provide reference for the research in sand liquefaction evaluation in other places.