Predicting the Compressive Strength of Concrete Using an RBF-ANN Model
In this study, a radial basis function (RBF) artificial neural network (ANN) model for predicting the 28-day compressive strength of concrete is established. The database used in this study is the expansion by adding data from other works to the one used in the author’s previous work. The stochastic...
Main Author: | Nan-Jing Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/14/6382 |
Similar Items
-
An ANN Model for Predicting the Compressive Strength of Concrete
by: Chia-Ju Lin, et al.
Published: (2021-04-01) -
Recycled Aggregates Concrete Compressive Strength Prediction Using Artificial Neural Networks (ANNs)
by: Mohamad Ali Ridho B K A, et al.
Published: (2021-01-01) -
Artificial Neural Network Model for Predicting Compressive
by: Salim T. Yousif, et al.
Published: (2013-05-01) -
Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete
by: Dong Van Dao, et al.
Published: (2020-02-01) -
The relationships between compressive strength and density of polystyrene lightweight concrete and their component ratios
by: Al-Lami Salman Mohammed, et al.
Published: (2021-01-01)