Genetic Regression Model for Dam Safety Monitoring  

大坝安全监控遗传回归模型研究及应用(英文)

作　　者：马震岳[1] 陈维江[2] 董毓新[1] 

机构地区：[1]大连理工大学土木建筑工程学院,大连116023 [2]中国水利水电科学研究院,北京100038

出　　处：《Transactions of Tianjin University》2002年第3期196-199,共4页天津大学学报（英文版）

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 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.根据大坝运行监测资料 ,通过逐步回归法建立的大坝安全监控模型普遍存在欠拟合问题 .本文在回归监控模型的基础上引入改进的遗传算法 ,对其回归系数进行寻优重估 ,建立遗传回归模型 .工程实例计算结果表明 。

关 键 词：dam safety monitoring under-fitting genetic regression model 

分 类 号：TV698.1[水利工程—水利水电工程]