RBF神经网络模型在大坝变形分析中的应用  

Application of RBF Neural Network Model in Dam Deformation Analysis

作　　者：唐加云 Tang Jia-yun(Hunan Zhimou Planning and Engineering Design Consulting Co.,Ltd.,Zhuzhou 412007,Hunan Province,China)

机构地区：[1]湖南智谋规划工程设计咨询有限责任公司,湖南株洲412007

出　　处：《科学与信息化》2023年第13期55-57,共3页Technology and Information

摘　　要：如今,水库大坝作为城市建设的主要基础设施,其安全问题受到越来越多人的关注,这也促使大坝安全监测工作越发重要。构建大坝变形分析的RBF神经网络并做好相应的预测,可有效提高模型预测的精度,还能更接近工程实际,具有极高的实用价值。针对此,本文围绕RBF神经网络模型进行了分析,对该模型在大坝变形分析中的应用进行了探讨。At present,as the main infrastructure of city construction,the safety of reservoir dam is receiving more attention by people,which makes the dam safety monitoring more important.The construction of RBF neural network for dam deformation analysis and the corresponding prediction can effectively improve the accuracy of model prediction,and is more close to engineering practice,with high practical value.In this paper,the RBF neural network model is analyzed and its application in dam deformation analysis is discussed.

关 键 词：RBF神经网络模型 大坝变形分析 应用 原理 

分 类 号：TV6[水利工程—水利水电工程]