Prediction of Later-Age Concrete Compressive Strength Using Feedforward Neural Network
Accurate prediction of the concrete compressive strength is an important task that helps to avoid costly and time-consuming experiments. Notably, the determination of the later-age concrete compressive strength is more difficult due to the time required to perform experiments. Therefore, predicting...
Saved in:
Main Authors: | Thuy-Anh Nguyen, Hai-Bang Ly, Hai-Van Thi Mai, Van Quan Tran |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | Advances in Materials Science and Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/9682740 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Prediction Compressive Strength of Concrete Containing GGBFS using Random Forest Model
by: Hai-Van Thi Mai, et al.
Published: (2021-01-01) -
Investigation of ANN Architecture for Predicting Load-Carrying Capacity of Castellated Steel Beams
by: Thuy-Anh Nguyen, et al.
Published: (2021-01-01) -
Compressive Strength Prediction of Stabilized Dredged Sediments Using Artificial Neural Network
by: Van Quan Tran
Published: (2021-01-01) -
Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks
by: Mehdi Nikoo, et al.
Published: (2015-01-01) -
Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model
by: Nhat-Duc Hoang, et al.
Published: (2016-01-01)