基于指数函数的非线性模型在路基沉降预测分析中的应用

摘要

针对指数曲线模型在表述路基沉降规律方面存在的不足，提出一种多项型指数曲线模型。对不同的沉降－时间数据列只需调整指数曲线模型项数便可取得理想拟合预测效果。先采用非线性最小二乘法估算模型的参数范围，再用遗传算法求最优值。工程实例表明，多项型指数曲线模型具有较高的预测精度，优于传统指数模型、双曲线模型、星野模型及灰色理论模型等，具有借鉴意义。%Aiming at the deficiency of the exponential curve model in describing the law of subgrade settlement,a multinomial exponential curve model was proposed. The different settlement time data columns only need to adjust the number of exponential curve model can achieve the ideal fitting effect. The range of parameters to the models was estimated by the nonlinear least square method,and the optimal value was obtained by using the genetic algorithm. Engineering examples showed that the model has higher prediction accuracy than the traditional index model,hyperbolic model,Hoshino model and gray theory model etc.,have reference significance.