Genetic regression Model For Dam Safety Monitoring

摘要

Under-fitting problems usually occur in regression models for dam safety monitoring. To overcome the local convergence of the regression, a genetic algorithm (GA) was proposed using a real parameter coding, a ranking selection operator, an arithmetical crossover operator and a uniform mutation operator, and calculated the least-square error of the observed and computed values as its fitness function. The elitist strategy was used to improve the speed of the convergence. After that, the modified genetic algorithm as applied to reassess the coefficients of the regression model and a genetic regression model was set up.