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可解释的机器学习和集合模型用于预测自强化混凝土的新特性

Maaz Khan1, Muhammad Faisal Javed1,2, Hisham Alabduljabbar3

  • 1Department of Civil Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan.

Scientific reports
|November 26, 2025
PubMed
概括

机器学习模型准确地预测了自凝固混凝土 (SCC) 的特性,减少了昂贵的实验测试. 基因表达编程 (GEP) 和深度神经网络 (DNN) 显示了高精度的低潮流和V道时间预测.

关键词:
深度神经网络是一种深度神经网络.基因表达编程 基因表达编程机器学习 机器学习混合设计优化,设计优化.风病学性质 风病学性质自强化混凝土的自强化混凝土

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