Intelligent Prediction Model (IPM) of Foundation Pit Displacement Based on Extreme Learning Machine (ELM) and Its Application

In order to effectively predict the dynamic displacement and disaster, according analysis of influencing parameters affecting deformation a subway foundation pit supported by piles (walls), rough set attribute reduction method (RSARM) average influence value algorithm (AIVA) are used simplify factors deformation. Those simplified taken as input ELM, with output being pit. Finally, IPM derived from ELM is obtained, which finally for engineering practice. The results show that it feasible RSARM AIVA. proposed has high accuracy good generalization ability, can be prediction.