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Updated: Jun 11, 2025

Surrogate Model Development for Digital Experiments in Welding
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预测高强度混凝土的压力强度:对人工神经网络,自适应神经模糊推理系统和响应表面方法学的比较研究

Tianlong Li1,2, Jianyu Yang1, Pengxiao Jiang3

  • 1School of Civil Engineering, Changsha University of Science & Technology, Changsha 410000, Hunan, China.

Materials (Basel, Switzerland)
|September 28, 2024
PubMed
概括

这项研究比较了机器学习和响应表面方法来预测高强度混凝土 (HSC) 的压力强度. 人工神经网络 (ANN) 在响应表面方法 (RSM) 和自适应神经模糊推理系统 (ANFIS) 上表现出更高的准确性.

关键词:
人工神经网络的人工神经网络中心复合设计设计的中心复合设计.压力强度压力强度的压力强度.高强度混凝土的混凝土神经模糊推理系统的神经模糊推理系统灵敏度分析是一种灵敏度分析.

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