Estimation of the Compressive Strength of Self-Compacting Concrete (SCC) by a Machine Learning Technique Coupling with Novel Optimization Algorithms
Self-compacting concrete (SCC), as a liquid aggregate, is suitable for use in reinforced constructions with no need for vibration. SCC utilization has been found in a wide range of projects. Nevertheless, those applications are often limited due to lacking the knowledge about such mixed materials, e...
Saved in:
Main Authors: | Ling Chen, Wengang Jiang |
---|---|
Format: | Article |
Language: | English |
Published: |
Bilijipub publisher
2023-03-01
|
Series: | Advances in Engineering and Intelligence Systems |
Subjects: | |
Online Access: | https://aeis.bilijipub.com/article_169079_f18ae755db20bf111558015abb48f2c0.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Modeling Compressive Strength of Self-Compacting Concrete (SCC) Using Novel Optimization Algorithm of AOA
by: Francisca Blanco, et al.
Published: (2024-09-01) -
Estimating the Pile Settlement Using a Machine Learning Technique Optimized by Henry's Gas Solubility Optimization and Particle Swarm Optimization
by: Saravana Kumar, et al.
Published: (2022-12-01) -
Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm
by: Rafiqul Islam, et al.
Published: (2024-12-01) -
Novel Optimization Algorithms Usage to Model the Compressive Strength of Ultra-High-Performance Concrete in Machine Learning Technique: Support Vector Regression
by: Tianhua Zhou, et al.
Published: (2023-06-01) -
The Optimal Machine Learning Model for the Precise Prediction of HighPerformance Concrete Strength Property
by: Yufeng Qian
Published: (2023-03-01)