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Performance prediction of the tunnel boring machine (TBM) in the construction of urban tunnels is under the consideration of tunnel experts due to its ability in minimizing the time and cost of the tunneling project implementation. The utilization factor of TBM is one of the most important factors, indicating the TBM performance. The present study provides an advanced intelligent model for predicting the utilization factor in order to evaluate the performance of TBM, hence, the aims of this study are to compare three prediction models including the multiple linear regression (MLR), artificial neural network (ANN) and hybrid algorithm of the neural network-particle swarm optimization (ANN-PSO) to determine the best prediction model. In the present research, data of the east–west section of the tunnel on line 7 of Tehran Subway were used as the case study and its utilization factor was calculated in 44 working days, and …