Predicting the compressive strength of steel fiber added lightweight concrete using neural network

By F. Altun, Oezguer Kisi, K. Aydin. 2008

142 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/654c54bff9b84e54199c86830d524ca6a98abf6d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. A. Pham
2. Yu-Hsin Lu
3. Chih-Fong Tsai
4. Jui-Sheng Chou
5. Amir Hossein Alavi
6. M. Z. Naser
7. Hadi Salehi
8. Rigoberto Burgueño

In Electrical and Electronic Engineering

1. Chih-Fong Tsai
2. Yu-Hsin Lu
3. A. Pham
4. Jui-Sheng Chou

Citations in the corpus

• Machine learning in concrete strength simulations: Multi-nation data analytics (2014, methodology): “Notably, researchers have applied or evaluated the capability of ANNs to predict strength and other concrete behaviors [29,30,32– 34].”