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基于ANN的碳纤维楠竹锚杆锚固力预测研究

DOI: 10.6052/1000-0879-12-186, PP. 40-45

Keywords: 碳纤维楠竹锚杆,锚固力,人工神经网络,BP,模型,正交试验设计,敏感性

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Abstract:

为减小对文物本体的破坏,本文基于新疆某土遗址加固保护中碳纤维楠竹锚杆锚固力原位测试试验,考虑锚杆直径、长度、倾斜角以及灌浆体强度、孔径、碳纤维缠绕间距等锚固力影响因素,利用人工神经网络(artificialneuralnetwork,ANN)的误差反向传播(backpropagation,BP)算法及MATLAB人工神经网络工具箱,建立了锚固力预测的智能模型;并以原位测试所得的数据为学习样本和检验样本,验证了该方法的适用性和可行性.将训练好的网络模型进行扩展计算,基于L25(56)正交表试验理论分析了锚固力对各影响因素的敏感性,为同类加固工程的实际应用提供参考依据.

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