Based on the measured data of Fengman dam deformations for many years

the artificial neural network evolved by a genetic algorithm was adopted for forecasting the dam deformation. The shortcomings of the traditional BP artificial neural network lie in the slowness in the convergence rate and the weakness in the generalization ability. Compared with the popular multi-factor regression model and BP artificial neural network

the forecasting model based on artificial neural network evolved by a genetic algorithm had the characteristics of accurately forecasting and global convergence. The practical application to Fengman concrete dam shows that

compared with a commonly used statistical method

the forecasting method proposed can obviously enhance the forecasting precision of dam deformation.