通过混合智能推进混凝土混合比例:一种多目标优化方法
Feixiang Chen1,2,3,4, Wangyang Xu4, Qing Wen1,2,3
1CCCC Second Harbor Engineering Company Ltd., Wuhan 430070, China.
Materials (Basel, Switzerland)
|October 14, 2023
概括
本研究介绍了混凝土混合物设计的混合智能建模方法,结合了人工神经网络 (ANN) 和遗传算法 (GA). 该方法优化了混凝土的性能和成本,提高了施工效率和精度.
科学领域:
- 土木工程和材料科学 土木工程和材料科学
- 计算智能和优化计算智能和优化
背景情况:
- 混凝土混合物设计对于结构性能和成本效益至关重要.
- 传统方法往往缺乏精确性和适应性,以满足复杂的优化目标.
- 计算智能的进步为优化材料设计提供了新的途径.
研究的目的:
- 为混凝土混合物设计开发一种新的混合智能建模方法.
- 使用人工智能预测混凝土的机械性能并优化混合比例.
- 创建一个实用的,基于人工智能的系统,用于高效的混凝土混合设计.
主要方法:
- 混合智能建模集成人工神经网络 (ANN) 和遗传算法 (GA).
- 基于GA的ANN参数的优化,以提高预测准确度 (R2 > 0.95).
- 使用Scipy库和GA-ANN进行多目标优化,以平衡压力强度和成本.
主要成果:
- 实现了混凝土机械性能 (R2>0.95,低RMSE和MAE) 的高预测精度.
- 成功优化混凝土混合物比例,以实现多目标目标,平衡强度和成本.
- 开发了一个用户友好的基于人工智能的系统,用于实际的混凝土混合设计.
结论:
- 混合GA-ANN方法为混凝土混合物设计提供了一种新且准确的方法.
- 开发的AI系统为优化混凝土属性和成本提供了实用解决方案.
- 这项研究促进了建筑行业混凝土混合设计的效率和精度.
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