Compressive Strength Prediction of Self-Compacting Concrete-A Bat Optimization Algorithm Based ANNs
This article examines the feasibility of using bat-trained artificial neural networks (ANNs) to predict the compressive strength of self-compacting concrete (SCC). The nonlinear behavior of SCC challenges traditional modeling techniques. Therefore, this work takes advantage of the superior predictiv...
Saved in:
Main Authors: | Amir Andalib, Babak Aminnejad, Alireza Lork |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | Advances in Materials Science and Engineering |
Online Access: | http://dx.doi.org/10.1155/2022/8404774 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predicting Shear Strength in FRP-Reinforced Concrete Beams Using Bat Algorithm-Based Artificial Neural Network
by: Mohammad Nikoo, et al.
Published: (2021-01-01) -
Modeling Compressive Strength of Self-Compacting Concrete (SCC) Using Novel Optimization Algorithm of AOA
by: Francisca Blanco, et al.
Published: (2024-09-01) -
Estimation of the Compressive Strength of Self-Compacting Concrete (SCC) by a Machine Learning Technique Coupling with Novel Optimization Algorithms
by: Ling Chen, et al.
Published: (2023-03-01) -
Compressive Strength Evaluation of Fiber-Reinforced High-Strength Self-Compacting Concrete with Artificial Intelligence
by: Tu T. Nguyen, et al.
Published: (2020-01-01) -
An investigation of the effect of high temperature on the strength compression and ultrasonic pulse velocity of self-compacting concrete
by: Hadji Ben Salah, et al.
Published: (2024-01-01)