Deformation prediction model of metal mine tailings dam based on GEP

Deformation monitoring of tailings dam is a very important part for metallic mine enterprises in production management. In view of the existing defects of tailings dam deformation prediction model, this paper has established the prediction model of tailings dam deformation based on GEP-Deep Excavation, and made a prediction for observation displacement in a certain metal mine tailings dam by GEP (Gene Expression Programming) algorithm with Eclipse as a development tool, through the process of selecting a set of functions, terminating character sets, population initialization, the chromosome decoding, fitness evaluation and genetic operation. By contrastive analysis of the gray GM(1,1) and BP neural network, empirical studies confirm the feasibility and effectiveness of the prediction model of tailings dam deformation based on GEP. This paper provides a new method for tailings dam deformation prediction of metal mine.