Research of combined grey model based on entropy weight for predicting anchor bolt bearing capacity

Abstract

Abstract A combined prediction model based on entropy weight was proposed to overcome the shortcomings of single grey model for predicting anchor bolt bearing capacity. Firstly, the grey GM (1,1) model and grey Verhulst model are used to predict the bearing capacity of anchor bolt according to the P-S curve obtained from pull test. Secondly, the entropy weight method is utilized to obtain the weight indexes of the two mode. Then two models are combined by the weight index to achieve final bearing capacity prediction. The experimental results show that the combined prediction model based on entropy weight can improve the accuracy of the grey prediction model as the load increasing.