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Indexed by:期刊论文

Date of Publication:2022-06-29

Journal:Transactions of Tianjin University

Affiliation of Author(s):建设工程学部

Volume:8

Issue:3

Page Number:196-199

ISSN No.:1006-4982

Abstract: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 was applied to reassess the coefficients of the regression model and a genetic regression model was set up. As an example, a slotted gravity dam in the Northeast of China was introduced. The computational results show that the genetic regression model can solve the under-fitting problems perfectly.

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