论文部分内容阅读
考虑到地基沉降预测模型中参数的时变特性及预测结果的可靠性,本文提出地基沉降概率预测方法:运用贝叶斯动态模型建立地基沉降过程的状态方程和观测方程,利用参数先验信息并结合含有噪声的前期沉降观测数据,对沉降状态参数进行Bayes后验概率推断,通过不断的“概率预测-修正”递推运算,获得最优沉降状态概率估计来预测地基沉降量。数值实例结果表明,与其他预测方法相比较,本文的方法是可行有效的。
Considering the time-varying characteristics of the parameters in the prediction model of foundation settlement and the reliability of the prediction results, this paper presents a prediction method of the probability of foundation settlement: using the Bayesian dynamic model to establish the state equations and observation equations of the settlement process, Combined with the pre-settlement observation data with noise, the Bayesian posterior probability estimation of settlement state parameters is carried out, and the optimal subsidence state probability estimation is obtained through continuous “Probabilistic Prediction-Correction” recursion calculation to predict the settlement of foundation. Numerical examples show that compared with other prediction methods, the proposed method is feasible and effective.