受腐蚀钢筋混凝土梁极限承载力神经网络预测

Prediction on ultimate load bearing capacity of corroded reinforced concrete beams using neural networks

利用神经网络方法研究了受腐蚀钢筋混凝土梁极限承载力与各主要影响因素之间的复杂非线性关系,建立了承载力的神经网络预测模型,预测结果与试验结果吻合较好.研究结果表明神经网络计算是受腐蚀钢筋混凝土构件力学性能研究中一种很有潜力的新方法.

Artificial Neural Networks (ANNs) technology was applied to build the complex non-linear relationship between the load bearing capacity of the corroded reinforced concrete beam and the main factors. BP Neural Networks model was built to predict the strength of the corroded beam. Satisfactory results are achieved. Therefore, it is proven that the neurocomputing is a practical and promising tool for the research on mechanical properties of the corroded reinforced concrete member.