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推进建筑3D打印与预测性层间粘合强度:一个堆叠模型范式.

Dinglue Wu1, Qiling Luo2,3,4, Wujian Long2,3,4

  • 1Poly Changda Engineering Co., Ltd., Guangzhou 510620, China.

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概括

使用堆叠策略的新机器学习 (ML) 模型提高了3D打印混凝土的质量. 该模型准确地预测了层间粘合强度 (IBS),改善了大型生产的混凝土稳定性.

关键词:
3D打印混凝土3D打印混凝土智能预测智能预测层间的粘合强度是层间的粘合强度.机器学习是机器学习.堆叠策略的策略堆叠策略.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 土木工程 土木工程是指土木工程.
  • 计算机科学 计算机科学

背景情况:

  • 对于实际应用,3D打印混凝土需要提高质量稳定性.
  • 准确预测层间粘合强度 (IBS) 对3D打印混凝土结构至关重要.

研究的目的:

  • 开发一种新的机器学习 (ML) 模型,用于预测3D打印混凝土的层间粘合强度 (IBS).
  • 为了提高3D打印混凝土的质量稳定性和生产可扩展性.

主要方法:

  • 实施一个堆叠机器学习策略.
  • 使用支向量回归 (SVR),K-最近邻居 (KNN) 和高斯过程回归 (GPR) 作为基本模型.
  • 使用十倍交叉验证和统计绩效评估.

主要成果:

  • 开发的堆叠模型在IBS预测中显著超过了个别基准模型.
  • 通过堆叠模型,确定系数 (R2) 从0.91提高到0.96.
  • 证明了层间粘合强度的卓越预测准确性.

结论:

  • 新型堆叠ML模型有效地提高了3D打印混凝土中层间粘合强度的预测准确性.
  • 这一进步有助于提高质量稳定性,并支持大规模生产3D打印混凝土结构.