摘要
软基路基沉降与其影响因素之间呈非线性关系。以某软基高速公路为例,以时段天数、时段载荷量及时段加载平均速率为解释变量,以时段沉降量为被解释变量,建立了非线性二次回归模型,并用遗传算法估算模型系数。工程实例表明,经遗传算法优化的非线性二次回归方程具有较高的预测精度,效果优于神经网络,用该模型进行软基高速公路沉降预测分析是可行的。
There is non-linear relationship between the settlement and the influence factors of soft subgrade.Taking a soft subgrade expressway as an example, taking the period of time, the load of time and the loaded average rate of time as the explanatory variables, and taking the settlement of time as the explained variable,the nonlinear quadratic regression model is established. And the genetic algorithm is used to estimate model coefficients. The engineering cases show that the nonlinear regression equation optimized by the genetic algorithm has the higher prediction accuracy, its effect is better than the neural network, and it is feasible to use this model for the forecast analysis of soft subgrade expressway settlement.
出处
《城市道桥与防洪》
2016年第10期149-151,18-19,共3页
Urban Roads Bridges & Flood Control
基金
兰州市科学技术局计划项目(兰财建发〔2015〕85号)
兰州石化职业技术学院科技资助项目(院发〔2015〕69号)
甘肃省科技厅计划项目(1204GKCA004)
甘肃省财政厅专项资金立项资助(甘财教〔2013〕116号)
关键词
路基沉降
二次回归方程
神经网络
遗传算法
预测分析
subgrade settlement
two regression equation
neural network
genetic algorithm
prediction analysis
