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人工神经网络在灌芯砌体抗压性能中的应用
Application of Artifical Neural Networks to Stress Behavior Trail of Grouted Block Masonry
【摘要】 提出基于径向基函数的人工神经网络方法,根据实验数据模拟灌芯砌体的抗压性能,建立模型,并验证了RBF神经网络在灌芯砌体抗压强度预估中具有良好的效果。结果显示,RBF神经网络在这方面有很好的应用前景。
【Abstract】 Base on the RBF artificial neural networks, the stress behavior trail of grouted block masonry can be modeled according to the experimental data, it sets up the model and proves the good effect with the experiment data. It shows the promising perspective of RBF Neural Networks in this way.
【关键词】 人工神经网络;
径向基函数;
灌芯砌体;
抗压强度;
【Key words】 Artifical Neural Networks; Radial Basis Function; Grouted Block Masonry; Stress Strength;
【Key words】 Artifical Neural Networks; Radial Basis Function; Grouted Block Masonry; Stress Strength;
- 【文献出处】 工程建设与设计 ,Construction & Design for Project , 编辑部邮箱 ,2005年02期
- 【分类号】TU364
- 【被引频次】2
- 【下载频次】45