The effect of clustering in improved soil resistance zoning in areas near fault

Geotechnical studies with a minimum of experiments can prevent from many of the problems caused by drilling such as the cost and blasting enormous in gas pipes. The spatial interpolation methods were developed for these problems with different applications. In most research on interpolation, the data used that the coefficient of variation are low, so in this study we have tried capability mapping interpolation methods for data with the coefficient of variation is relatively high, such as resistance allowed the soil near the fault tested and the impact of clustering method to improve the zoning evaluated. Eram town in Tabriz city selected as a case study because of its proximity to the main fault with nonisotropic data's. For this purpose, in this study, various methods such as kriging, inverse distance weighted, radial basis functions, local polynomial for zoning and cluster analysis with Euclidean distance with minimum variance technique is used. The data used for soil authorized strength of 40 boreholes in the town of Tabriz city. Zoning for the first state is without clustering and second state is with clustering that the whole area is divided into three zones. The result shows clustering approach could improve results and estimates at least 2 percent of estimate and at least 5 percent of root mean square error. The interpolation methods, local polynomial function method is better than other methods.