应用BP网络预测混凝土中的钢筋锈蚀量

Prediction for Corrosive Degree of Reinforcement in Concrete by Neural Network

钢筋锈蚀是影响混凝土结构耐久性的重要因素之一。本文通过建立BP网络模型对钢筋的锈蚀量进行计算和预测 ,并与目前常用的鉴别和检测方法相比较 ,结果表明建立BP网络是一种可以定量分析、简便易行的预测方法。

Corrosive degree of reinforcement in concrete is one of the main factors wihich influences the durability of the structure.In this paper,the corrosive degree can be evaluated and forecasted by the model of BP neural network,which is compared with the methods used usually in ur country.The conclusion is that setting BP neural network is a convenient forecasting method which can be used to analyze in number.