改进灰色马氏组合模型在建筑物沉降预测中的应用

Application of Improved Grey Markov Model in Building Settlement Prediction

结合青岛某工程大厦实测数据,提出了基于小波去噪的改进灰色-马尔柯夫组合模型,对建筑物进行沉降预测。首先,采用小波变换理论对数据进行小波去噪;然后,利用Matlab建立新陈代谢灰色模型,并对去噪数据进行沉降预测;最后,将新陈代谢灰色模型得到的相关预测值划分为不同的状态区间,再利用马尔科夫模型来确定最终的沉降预测值。结果表明,组合模型的预测精度和预测结果要优于其他两个模型,且其稳定性和可靠性都有很大提高。

Combined with the measured data of a certain engineering building in Qingdao,an improved grey-Markov combined model based on wavelet denoising is proposed to predict the settlement of buildings.Wavelet denoising is first applied to the data using wavelet transform theory.Then use Matlab to establish a metabolic gray model and predict the sedimentation data.Finally,the relevant prediction values obtained from the metabolic gray model are divided into different state intervals,and then the Markov model is used to determine the final settlement prediction value.The results show that the prediction accuracy and prediction results of the combined model are better than the other two models,and the stability and reliability are greatly improved.