人工神经网络预测合规系数的复合切割钥匙的建筑木梁的木梁
Irene A Ladnykh1, Nabi Ibadov1, Hubert Anysz1
1Faculty of Civil Engineering, Warsaw University of Technology, 00-661 Warsaw, Poland.
Materials (Basel, Switzerland)
|July 13, 2024
概括
这项研究使用人工神经网络 (ANN) 来预测木梁剪切钥匙的合规系数. 这项创新增强了建筑木梁的设计,改善了结构分析和建筑应用.
科学领域:
- 结构工程 结构工程
- 材料科学 材料科学 材料科学
- 计算力学 计算力学 计算力学
背景情况:
- 复合切割键对于建筑木材梁的性能至关重要.
- 现有的木梁与剪切键的设计方法需要准确的合规系数.
- 预测这些系数对于现代建筑应用是必不可少的.
研究的目的:
- 开发一个预测模型,用于构建木梁中的复合剪切键的合规系数.
- 分析和结合现有的关于合规系数的实验数据.
- 为此预测任务提出一个人工神经网络 (ANN) 架构.
主要方法:
- 文献审查和对实验合规系数值的数据汇编.
- 为ANN培训和验证创建一个新的数据集.
- 开发和测试一个特定的ANN架构.
主要成果:
- 创建了一个全面的合规系数数据集.
- 一个ANN架构被提出并验证.
- 实现了高度准确的预测,平均绝对百分比误差为kw的0.054%和ki的0.052%.
结论:
- 开发的ANN模型准确地预测了复合切割钥匙的合规系数.
- 这种方法为设计建筑木梁提供了一个实用的工具.
- 这些发现有助于推进现代建筑中木材的使用.
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