【摘要】 为简化震害预测工作,提出一种以房屋普查数据为震害影响因子并利用人工神经网络模型为工具的震害预测方法。从以往震害实例中选取了具有典型破坏特点的建筑物作为神经网络的学习样本,用收集的数据对网络进行了训练并得到了收敛的网络,应用此收敛的网络对一组新的房屋数据进行震害预测,结果表明了运用此方法和模型的实用性。更多还原

【Abstract】 For the aim of simplifying the work of seismic disaster predicting,a method for predicting a city’s buildings’ seismic disaster is presented.The general survey data of buildings as factors affecting buildings’ seismic disaster and artificial neural network as a tool to calculate the seismic disaster were used.Typical destroyed buildings were collected as samples from many previous earthquakes.After training the model using the collected data a convergent model was acquired.It has been proved that the model was sufficient for predicting buildings’ seismic disaster after using it to predict the seismic disaster of a group of new buildings.更多还原