基于房屋普查数据的震害预测方法

Study on the Seismic Disaster Prediction Based on General Survey Data of Buildings

提出了一种利用人工神经网络模型并以房屋普查数据为震害影响因子的震害预测方法。以建筑物的结构类型、层数、高度、建设年代、用途、现状质量等几个简单参数对城市、建筑物进行分类,并在此基础上进行建筑物的震害预测工作。根据震害因子的选取及网络对样本的训练效果建立一个人工神经网络模型,通过此模型对震害实例的预测结果进行分析,证明了此模型的实用性。利用房屋普查数据进行震害预测工作为研究快速震害预测方法提供了一个新的思路。

In this article, with artificialneural networknmodel and general survey tlata of buildings as seismic disas terfactor, a method of the seimic disaster prediction is brought forward. Basing on several simple parameters of conthe struction, such as structure types, stories, heights, age of construction, uses, present condition quantity and so on seismic disater prediction is carrying on. According to the selection of seismic disaster factor and the training results of the net, an artificial neural network model is set up. The model was proved to be work ability according to the seismic disaster prediction results after using it in some seismic disaster examples. A new way of thinking of rapid seismic disaster prediction is given by using general survey data of buildings.