Predicting the ultimate bearing capacity of anchor bolt is the most important part in the bearing capacity prediction of the anchor bolt. In traditional methods

the elastoplastic stage experimental data are usually from pull-out tests on anchor bolts used to predict bearing capacity. However

in practice

it is not easy to discriminate the elastic stage from elastoplastic stage

and additionally the actual P-S curves usually have various shapes. Thus

the single model is difficult to accurately predict all kinds of anchor bolts ultimate bearing capacity. Since the prediction of ultimate bearing capacity belongs to an uncertain problem

a combined forecasting model is developed with the Dempster-Shafer(D-S) evidence theory fusion algorithm that is widely used in the multi-sensor information fusion. The D-S theory is an efficient method to process uncertain incomplete and vague information in data fusion. The aim of the management of uncertainty in a system is to reach the best approximation. The D-S algorithm firstly employs a complete set consisting incompatible basic hypothesis to represent all possibilities

and assigns the basic possibility of confidence. Then

the D-S combination rules is applied to calculate the confidence of the new evidence body reflecting the combination of information produced by the same proposition with various evidence. Finally

the best approximation of the "uncertainty" will be determined by analyzing the confidence of new evidence body generated by each proposition. This paper

by reducing the elastic phase data

enables each prediction model participating in combination generate many predicted values

and then supposes each predicted value as an evidence

with the same identification framework. Moreover

it combines the evidence with the same type but different characteristics into a new evidence accordance with the D-S combination rules

and obtains the final prediction results according to the decision rules. Comparing the D-S method with traditional arithmetic mean method

the results show that the prediction accuracy using the D-S method is more accurate. As the prediction values are easily influenced by the given initial value

the modified prediction method in this paper shows that the modified method has higher precision. The results can be used for mine construction

underground construction

subsequent quality testing

stability evaluation and rock strength prediction.