Optimized artificial neural network model for accurate prediction of compressive strength of normal and high strength concrete
This study develops and presents an Artificial Neural Network (ANN) model employing the Levenberg-Marquardt Backpropagation (LMBP) training algorithm to predict the compressive strength of both normal and high strength concrete. The model's robustness was evaluated using an extensive dataset co...
Main Authors: | Arslan Qayyum Khan, Hasnain Ahmad Awan, Mehboob Rasul, Zahid Ahmad Siddiqi, Amorn Pimanmas |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-12-01
|
Series: | Cleaner Materials |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2772397623000448 |
Similar Items
-
Determination of the Compressive Strength of Concrete Using Artificial Neural Network
by: Jose Manuel Palomino Ojeda, et al.
Published: (2021-06-01) -
PREDICTION OF THE COMPRESSIVE STRENGTH OF ENVIRONMENTALLY FRIENDLY CONCRETE USING ARTIFICIAL NEURAL NETWORK
by: Monika KULISZ, et al.
Published: (2022-12-01) -
Effect of glass powder on the compression strength and the workability of concrete
by: Afif Rahma, et al.
Published: (2017-01-01) -
An ANN Model for Predicting the Compressive Strength of Concrete
by: Chia-Ju Lin, et al.
Published: (2021-04-01) -
Compressive Strength Prediction of Rubber Concrete Based on Artificial Neural Network Model with Hybrid Particle Swarm Optimization Algorithm
by: Xiao-Yu Huang, et al.
Published: (2022-05-01)