本文利用BP神经网络模型，对部分预应力混凝土矩形截面梁裂缝宽度的计算方法进行了探讨。首先，通 过理论分析，找出影响预应力混凝土梁裂缝宽度的主要因素，在此基础上，建立预测预应力混凝土梁裂缝宽度 的优化BP神经网络模型。然后，针对所建模型，输人一定量的实测的预应力混凝土梁裂缝宽度数据样本，进行 模型参数的训练和学习，利用人工元神经网络的特点，训练好裂缝宽度计算模型。仿真计算的结果表明，应用人 工元神经网络方法，进行部分预应力混凝土梁的裂缝宽度的预测计算是可行的，而且与我国现行规范公式的计 算结果相比，计算精度更高。

In this paper, the crack width of partly prestressing concrete square-section beam under the bending moment is explored by BP neural network. Firstly, by theoretical analyzing and testing BP neural network, the main effect factors that influence the crack width are found and other second-class effect factors are neglected. The optimized BP neural network is created, and more influential factors can be considered in the mode at the same time and the method of predit the crack width by BP Neural Network is discussed. Training and simulating with different samples show that the results are in accordance with the actual data well. It can be seen that it is feasible and precise to predict the crack width of partly prestressing forcing concrete square- section beam under the bending moment by BP neural network, and it is much better than using the calculation formula of the china's code for design of concrete structures