Application of machine learning boosting and bagging methods to predict compressive and flexural strength of marble cement mortar-Reference-Cited by-同舟云学术

Application of machine learning boosting and bagging methods to predict compressive and flexural strength of marble cement mortar

Published:2024-06 Issue: Volume:39 Page:108600
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Chen Zhiqiang

Publisher

Elsevier BV

Reference56 articles.

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1. Experimenting the effectiveness of waste materials in improving the compressive strength of plastic-based mortar;Case Studies in Construction Materials;2024-12

2. Optimizing machine learning techniques and SHapley Additive exPlanations (SHAP) analysis for the compressive property of self-compacting concrete;Materials Today Communications;2024-06

3. Analyzing the efficacy of waste marble and glass powder for the compressive strength of self-compacting concrete using machine learning strategies;REVIEWS ON ADVANCED MATERIALS SCIENCE;2024-01-01

4. Evaluating the strength loss and the effectiveness of glass and eggshell powder for cement mortar under acidic conditions;REVIEWS ON ADVANCED MATERIALS SCIENCE;2024-01-01