基于MATLAB的深基坑沉降监测预报模型优选  

The preferred model base on MATLAB for settlement observation and prediction of deep foundation pits

作　　者：尤军[1] 殷耀国[1,2] 李辉 柳永全 

机构地区：[1]宁夏大学土木与水利工程学院,银川750021 [2]旱区现代农业水资源高效利用教育部工程研究中心,银川750021 [3]宁夏博源科奥测绘技术有限公司,银川750004

出　　处：《中国科技论文》2015年第15期1772-1777,共6页China Sciencepaper

摘　　要：沉降监测预报需要准确、及时和有效。针对沉降监测预报模型种类较多,导致数据处理和预报模型选用的随意性较大,提出了沉降监测预报模型的优选。以宁夏3个深基坑工程实际监测数据为案例,分别采用MATLAB中5种曲线拟合模型和3种人工神经网络模型进行预报,通过对比优选出适合的沉降监测预报模型。结果表明:GR(general regression)神经网络模型预报效果最好,BP(back propagation)神经网络模型和RBF(radial basis function)神经网络模型预报效果较好;BP神经网络模型的沉降预报精度比RBF神经网络模型稍高;三次样条插值模型可以进行沉降预报,但预报效果不及神经网络模型;采用不同模型进行联合预报,可以增强预报的可靠性;在工程实践中,发挥人工神经网络3种模型的预报优势,进行周期性预报和实时安全评价,具有一定实际意义。Settlement observation and prediction requiress accuracy and timeliness in order to be effective.To amalgamate the many types of settlement observation and prediction modeling,which result in an arbitrarily large array of data processing and forecasting model options,a method for the optimization of the model of settlement monitoring and forecasting is proposed.Three case study examples of deep foundation pits in Ningxia,China were used in five kinds of MATLAB curve fitting models and three kinds of artificial neural network models in order to predict,by contrast,the optimized model base for settlement observation. The results show that the general regression （GR）neural network model predicted best,that the back propagation （BP）neural network and radial base function （RBF）neural network models forecasted better,that the BP neural network model’s accuracy for settlement observation was better than the RBF neural network model’s and that the cubic spline interpolation model can be settlement prediction but its forecast effect is not as good as neural network model’s.Also,the results indicate that using differ-ent models for joint forecasting can enhance the reliability of forecasts.In the practice of engineering,the capacity for prediction in the three artificial neural network models,as well as their periodic forecasting and real-time safety assessment,has practical significance.

关 键 词：沉降监测预报 MATLAB 曲线拟合 人工神经网络 

分 类 号：TU433[建筑科学—岩土工程]