介绍使用GEP估计现场造堆中的自压缩混凝土的立方压力强度的模型
Hossein Maleki Toulabi1, Seyed Azim Hosseini2
1Department of Civil Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.
Scientific reports
|October 29, 2024
概括
这项研究使用基因表达编程预测了在现场造堆中的自压缩混凝土 (SCC) 的压力强度 (CS). 开发的模型准确地估计了SCC.
科学领域:
- 土木工程 土木工程是指土木工程.
- 材料科学 材料科学 材料科学
背景情况:
- 现场造堆是土木工程中至关重要的深层基础.
- 堆中的普通混凝土面临着压力强度 (CS) 降低和透性增加等挑战.
- 自压缩混凝土 (SCC) 提供了更好的CS,压缩和更快的堆施工.
研究的目的:
- 研究在现场造堆中对自压缩混凝土 (SCC) 的压力强度 (CS) 的预测.
- 使用实验室数据和软计算技术,开发SCC CS的预测模型.
主要方法:
- 利用了实验室数据和软计算技术.
- 实现了一个基因表达编程 (GEP) 模型,具有7个输入参数.
- 使用神经网络分析来评估模型性能.
主要成果:
- 使用开发的模型实现了 99.98% 的高预测准确度.
- 基因表达编程模型有效地估计了堆中的SCC的CS.
- 证明了模型在预测SCC压力强度方面的精度.
结论:
- 开发的GEP模型准确地预测了SCC在现场造堆中的压力强度.
- 这种预测工具可以帮助工程师和研究人员设计和建造具有所需SCC特性的堆.
- 该研究强调了软计算在优化混凝土基础设计方面的潜力.
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