摘要
目前,基于BP神经网络法进行冻土路基变形预测的可行性和有效性仍少有学者对其进行研究。运用MATLAB编制BP神经网络程序,并应用于青藏铁路预测路基变形的工程实例。在此基础上,又采用COMSOL有限元软件的多场耦合模块分析了同一路基的变形场、水热场。通过对比两种方法,验证了前者的科学性和有效性。进而提出了一种新的可靠度计算方法(INNRS法),这种方法将神经网络法和响应面法有机结合起来,只需一次迭代即可形成较准确的功能函数,使得计算可靠指标的效率大大提高。应用INNRS法,对路基变形的可靠度指标和失效概率进行了评价。
Few researches have been conducted on the feasibility and effectiveness of BP neural network method on the deformation prediction of subgrade in frozen region. In this study,the Qinghai-Tibet railway subgrade was taken as an example,and the hydrothermal field and deformation field of the subgrade were simulated and analyzed using the finite element software COMSOL. The simulation results were then used to verify the BP neural network model programmed by MATLAB. Furthermore,an improved neural network response surface method(INNRS) was proposed by combining the neural network and the response surface method. Numerical simulations disclose that the INNRS method can achieve the performance function with good accuracy only in one iteration. It can be applied to practical assessment on reliability index and probability of failure and subgrade in frozen region.
引文
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