An artificial neural network model for predicting compression strength of heat treated woods and comparison with a multiple linear regression model
By S. Tiryaki, Aytaç Aydın. 2014
138 citations recorded by the source corpus.
Subfields: Building and Construction, Civil and Structural Engineering, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/419e17336e238c1d26f3f68cef26377d4802452e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Building and Construction
In Civil and Structural Engineering
- A. Pham
- Yu-Hsin Lu
- Chih-Fong Tsai
- Jui-Sheng Chou
- Amir Hossein Alavi
- M. Z. Naser
- Hadi Salehi
- Rigoberto Burgueño
In Mechanical Engineering
Citations in the corpus
- Machine learning in concrete strength simulations: Multi-nation data analytics (2014, methodology): “The many prediction techniques proposed so far include empirical models, statistical techniques and artificial intelligence algorithms [3,8,10,13,21,29].”