CBeamXP: Continuous Beam Cross-Section Predictors

<b>CBeamXP: </b><b>Continuous Beam Cross-section Predictors dataset</b>The <b>CBeamXP </b>(<b>C</b>ontinuous <b>B</b><b>eam</b> Cross-section (<b>X</b>) <b>P</b>redictors) is a dataset containing 1,000,000 data-points to be used for machine learning research. Each data-point represents an Ultimate Limit State (ULS) compliant beam from a continuous system consisting out of 11 members with utilisation ratios between 0.97 to 1.00. The predictors include span and uniformly distributed loads (UDLs) which can be used to predict the cross-sectional properties of each beam contained within the dataset. This dataset is publicly available on a <b>CC-BY-4.0</b> licence and was used within the <b>Gallet et al. (2024)</b> journal article "Machine learning for structural design models of continuous beam systems via influence zones" (doi.org/10.1088/1361-6420/ad3334). Publications making use of the CBeamXP dataset are requested to cite the aforementioned journal article.In addition to the dataset, a training script, environment YAML file and a collection of saved models developed in the Gallet et al. (2024) study are available. These can be used to quickly generate user defined neural networks, compare performances and verify the results achieved by the Gallet et al. (2024) investigation.There are 5 files in this directory:CBeamXP_dataset.csvGallet_2024_training_script.pyGallet_2024_environment.ymlREADME.txtsaved_models.zipClick "Download all" (button at the top) to download the files and and look at the README.txt file for further details on the dataset and how to use the training script.

**CBeamXP：连续梁截面预测器数据集（Continuous Beam Cross-section Predictors dataset）**

CBeamXP（Continuous Beam Cross-section Predictors）是一款面向机器学习研究的数据集，共计包含100万个数据点。每个数据点均对应一个符合极限承载力状态（Ultimate Limit State，ULS）要求的梁，该梁取自由11个构件组成的连续体系，其荷载利用率比介于0.97至1.00之间。本数据集的预测变量涵盖跨度与均布荷载（Uniformly Distributed Loads，UDLs），可用于预测数据集中各梁的截面特性。

本数据集采用CC-BY-4.0协议公开授权，已被应用于Gallet等人（2024）发表的期刊论文《基于影响域的连续梁体系结构设计模型的机器学习研究》（原文标题："Machine learning for structural design models of continuous beam systems via influence zones"，DOI：10.1088/1361-6420/ad3334）。使用本CBeamXP数据集的研究成果，请引用上述期刊论文。

除数据集本体外，本资源包还包含Gallet等人（2024）研究中开发的训练脚本、环境配置YAML文件以及一组已保存的模型。这些资源可用于快速生成自定义神经网络、对比模型性能，并复现Gallet等人（2024）研究的实验结果。

本目录中共包含5个文件：
CBeamXP_dataset.csv
Gallet_2024_training_script.py
Gallet_2024_environment.yml
README.txt
saved_models.zip

点击页面顶部的「全部下载」按钮即可获取所有文件，详细的数据集说明与训练脚本使用方法请参阅README.txt文件。