Applying a meta-heuristic algorithm to predict and optimize compressive strength of concrete samples
The successful use of fly ash (FA) and silica fume (SF) materials has been reported in the design of concrete samples in the literature. Due to the benefits of using these materials, they can be utilized in many industrial applications. However, the proper use of them in the right mixes is one of th...
Saved in:
Main Authors: | Lei, Sun, Koopialipoor, Mohammadreza, Armaghani, Danial Jahed, Tarinejad, Reza, Tahir, M. M. |
---|---|
Format: | Article |
Published: |
Springer Science and Business Media Deutschland GmbH
2021
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/94581/ http://dx.doi.org/10.1007/s00366-019-00875-1 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Investigating the effective parameters on the risk levels of rockburst phenomena by developing a hybrid heuristic algorithm
by: Zhou, Jian, et al.
Published: (2021) -
Two novel combined systems for predicting the peak shear strength using RBFNN and meta-heuristic computing paradigms
by: Gao, Juncheng, et al.
Published: (2022) -
Prediction of cement-based mortars compressive strength using machine learning techniques
by: Asteris, Panagiotis G., et al.
Published: (2021) -
Random forest and bayesian network techniques for probabilistic prediction of flyrock induced by blasting in quarry sites
by: Han, Han, et al.
Published: (2020) -
Application of several optimization techniques for estimating tbm advance rate in granitic rocks
by: Armaghani, Danial Jahed, et al.
Published: (2019)