• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>BioTechnology: An Indian Journal >Application of BP neural network for the design of isolated structure
【24h】

Application of BP neural network for the design of isolated structure

机译：BP神经网络在隔震结构设计中的应用

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The effects of local construction of isolation layer on the overall architecture are described in this thesis. Nowadays, the earthquake is a great problem in the world, for it can not be predicted. The only thing we can do is to enhance the ability to resist the earthquake. So, the first thing of all is to improve the seismic performance of buildings. Based onBP neural network, a preliminary design system for isolation is established with the seismic fortification type, seismic fortification intensity, site classification, seismic grouping, the depth-width ratio, the length-width ratio, ground floor stiffness, mass and area as the main influencing factors, and the largest layer shear force ratio of the structure after isolation and the largest displacement as output results.After the network training with 25 training samples, the network test is done by 15 test samples. By the comparison of the test results with the actual design results, it is acknowledged that the average accuracy rate of neural network reaches 96%, which shows the analysis on the damping effect that the system of preliminary isolation design based on BP neural network has on isolated structure has high efficiency and accuracy.
机译：本文描述了隔离层的局部构造对整体架构的影响。如今，地震已成为世界性的大问题，因为无法预测。我们唯一能做的就是增强抗震能力。因此，首先要提高建筑物的抗震性能。基于BP神经网络，建立了以地震设防类型，地震设防强度，场地分类，地震分组，纵宽比，长宽比，地面刚度，质量和面积为基础的隔震初步设计系统。主要的影响因素是隔震后结构的最大层剪力比和最大位移作为输出结果。对25个训练样本进行网络训练后，对15个测试样本进行网络测试。通过将测试结果与实际设计结果进行比较，可以确认神经网络的平均准确率达到96％，这说明了基于BP神经网络的初步隔离设计系统对阻尼的影响。隔离结构具有较高的效率和准确性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号