Работы, цитирующие эту работу

Работ: 3

Работа: Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models

1. Performance prediction and analysis of engineered cementitious composites based on machine learning

   Wenguang Chen, Роман Федюк, Jie Yu +4

   СтатьяInnovative concrete reinforcement materialsDevelopments in the Built Environment2024Цитирований: 2

   ABIABI:AkademIndex/openalex/2024.article.000297

2. Tribological Properties Assessment of Metallic Glasses Through a Genetic Algorithm-Optimized Machine Learning Model

   Untung Rahardja, Arif Sarı, Ali Alsalamy +3

   СтатьяMetallic Glasses and Amorphous AlloysMetals and Materials International2023Цитирований: 0

   ABIABI:AkademIndex/openalex/2023.article.000099

3. Prediction of early age compressive strength of concrete using machine learning

   Ashok Kumar Palanisamy, D. Jegatheeswaran, Christo Ananth +4

   СтатьяConcrete Properties and BehaviorScientific Reports2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.001432