基于数据挖掘的房屋建筑健康态势预测

Prediction of Housing Construction Health Based on Data Mining

为了预防和降低房屋沉降不均等因素造成房屋坍塌事件,需要对房屋建筑健康态势进行预测。采用传统预测方法对房屋建筑健康态势进行预测时,忽略了房屋建筑沉降值的修正,导致预测结果准确率低、预测效率低的问题。针对以上问题,提出一种基于数据挖掘的房屋建筑健康态势预测方法。采用预测模型对房屋建筑各个部分的沉降进行组合预测,通过BP神经网络对组合模型预测得到的沉降值进行修正,根据修正后的房屋建筑沉降值完成对房屋建筑健康态势预测。实验结果表明,所提方法预测结果准确率高、预测效率高。

In order to prevent and reduce the collapse of houses caused by uneven settlement of houses,it is necessary to predict the health situation of building construction.When traditional forecasting methods predict the health of building construction,Ignore the correction of the settlement value of the building,lead to low accuracy of prediction results,poor prediction efficiency.Aiming at the above problems,this paper proposes a method prediction of housing construction health based on data mining.The prediction model is used to combination prediction the settlement of each part of the building.The settlement value predicted by the combined model is corrected by BP neural network.According to the revised settlement value of the building,the health situation prediction of the building is completed.The experimental results show that the proposed method has high accuracy and high prediction efficiency.