摘要
针对深基坑变形控制系统中的不确定性、模糊性因素多的问题,将模糊控制理论与神经网络技术相结合,采用非线性神经元构成的神经网络结构,把对应的网络输入、输出表达为输入、输出信息的模糊数隶属度,建立了一种基于模糊神经网络的深基坑施工变形预测模型.结果表明,利用模糊度隶属函数对基坑施工进行动态控制具有较好的实用效果.
Seeing that there are many uncertain and fuzzy factors in the deformation control system of excavation, this paper combines the fuzzy theory with neural network technology, adopts the neural network structure formed with non-linear neuron, and expresses corresponding network input and output into fuzzy degree number of input and output information. Thus according to fuzzy neural network, a displacement forecast model has been set up. The results show that using fuzzy degree number functions to conduct dynamic control over excavation construction has good practical effects.
出处
《重庆工学院学报（自然科学版）》
2008年第6期39-42,共4页
Journal of Chongqing Institute of Technology
关键词
深基坑
变形控制
模糊控制
神经网络
隶属度
excavation
deformation control
fuzzy control
neural network
degree number
作者简介
王万通（1981-），男，陕西西安人，主要从事建筑结构研究．
