Adaptive machine learning framework: Predicting UHPC performance from data to modelling
Ultra-High Performance Concrete (UHPC) is vital for next-generation infrastructure, necessitating complex interaction modeling beyond empirical methods. This study proposes an interpretable machine learning (ML) framework to predict the compressive strength (CS) of UHPC and analyze input variable in...
Saved in:
| Main Authors: | Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025027914 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing shear strength predictions of UHPC beams through hybrid machine learning approaches
by: Sanjog Chhetri Sapkota, et al.
Published: (2025-08-01) -
Performance assessment of UHPC composite barriers under velocity impacts
by: Viet Chinh Mai, et al.
Published: (2025-12-01) -
An interpretable machine learning model for predicting depression in middle-aged and elderly cancer patients in China: a study based on the CHARLS cohort
by: Yue Xiao, et al.
Published: (2025-07-01) -
Implementasi Algoritma Catboost Dan Shapley Additive Explanations (SHAP) Dalam Memprediksi Popularitas Game Indie Pada Platform Steam
by: Mohammad Teddy Syamkalla, et al.
Published: (2024-08-01) -
Malnutrition mediates the association between handgrip status and asthma risk: an observational and prospective cohort study from multiple European countries
by: Jun Wen, et al.
Published: (2025-07-01)