Novel Optimization Algorithms Usage to Model the Compressive Strength of Ultra-High-Performance Concrete in Machine Learning Technique: Support Vector Regression
Ultra-High-Performance Concrete (UHPC) is a resistant ingredient in projects requiring analysis of its composition to appraise the UHPC Compressive Strength (CS). Experimentally, assigning the relations between ingredients may require more time, energy, and cost. The intelligent techniques evaluate...
Saved in:
Main Authors: | Tianhua Zhou, Dorota Mozyrska |
---|---|
Format: | Article |
Language: | English |
Published: |
Bilijipub publisher
2023-06-01
|
Series: | Advances in Engineering and Intelligence Systems |
Subjects: | |
Online Access: | https://aeis.bilijipub.com/article_173618_91808e739673be0fa4bba419c684ded4.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Optimal Machine Learning Model for the Precise Prediction of HighPerformance Concrete Strength Property
by: Yufeng Qian
Published: (2023-03-01) -
Modeling Compressive Strength of Self-Compacting Concrete (SCC) Using Novel Optimization Algorithm of AOA
by: Francisca Blanco, et al.
Published: (2024-09-01) -
Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm
by: Rafiqul Islam, et al.
Published: (2024-12-01) -
The Implementation of a Support Vector Regression Model Utilizing Meta-Heuristic Algorithms for Predicting Undrained Shear Strength
by: Rami Al-Qasimi, et al.
Published: (2024-12-01) -
Appraising the Pile Settlement Rates by Support Vector Regression Optimized Using the Novel Optimization Algorithms
by: Argyros Maris
Published: (2023-06-01)