硅酸盐通报2024，Vol.43Issue(10)：3634-3644,11.
基于AutoML-SHAP的超高性能混凝土抗压强度可解释预测
Interpretable Prediction of Compressive Strength of Ultra-High Performance Concrete Based on AutoML-SHAP
摘要
Abstract
The correlations between compressive strength of UHPC and its mixture composition exhibit pronounced nonlinearity,presenting a challenge for analysis through conventional statistical approaches.In this study,an automatic machine learning(AutoML)technology was proposed to predict compressive strength of UHPC,and shapley additiveex planations(SHAP)was introduced to explain the AutoML model.The integration of AutoML and SHAP offered synergistic benefits,facilitating the development of a precise,efficient,and comprehensively interpretable model.Results demonstrate that AutoML model is automatically built with better accuracy and robustness than the base model.SHAP provides a global explanation,a single sample explanation,and a feature dependence explanation of characterization factors,which explains mechanism of the effect of each characterization factor on compressive strength.SHAP contributes to the understanding of mechanism of UHPC compressive strength development and the importance of characteristic factors,and can provide assistance in the design and application of UHPC.关键词
超高性能混凝土/抗压强度/机器学习/AutoML/SHAPKey words
ultra-high performance concrete/compressive strength/machine learning/AutoML/SHAP分类
信息技术与安全科学引用本文复制引用
李硕,艾丽菲拉·艾尔肯,罗文波,陈锦杰..基于AutoML-SHAP的超高性能混凝土抗压强度可解释预测[J].硅酸盐通报,2024,43(10):3634-3644,11.基金项目
国家自然科学基金(12072308) （12072308）
