Estimation of the soil liquefaction potential through the Krill Herd algorithm

Looking from the past to the present, the earthquakes can be said to be type of disaster with most casualties among natural disasters. Soil liquefaction, which occurs under repeated loads such as earthquakes, plays a major role in these casualties. In this study, analytical equation models were developed to predict the probability of occurrence of soil liquefaction. In this context, the parameters effective in liquefaction were determined out of 170 data sets taken from the real field conditions of past earthquakes, using WEKA decision tree. Linear, Exponential, Power and Quadratic models have been developed based on the identified earthquake and ground parameters using Krill Herd algorithm. The Exponential model, among the models including the magnitude of the earthquake, fine grain ratio, effective stress, standard penetration test impact number and maximum ground acceleration parameters, gave the most successful results in predicting the fields with and without the occurrence of liquefaction. This proposed model enables the researchers to predict the liquefaction potential of the soil in advance according to different earthquake scenarios. In this context, measures can be realized in regions with the high potential of liquefaction and these measures can significantly reduce the casualties in the event of a new earthquake.

Automated summary

Soil liquefaction, a type of disaster that often occurs during earthquakes, causes the highest number of casualties among natural disasters. This study developed analytical equation models to predict the probability of soil liquefaction, using earthquake and ground parameters determined from real field conditions. Among the developed models, the Exponential model showed the most accurate results in predicting the occurrence of liquefaction, based on earthquake magnitude, fine grain ratio, effective stress, standard penetration test impact number, and maximum ground acceleration parameters.