Optimizing ANN performance using DOE: application on turning of a titanium alloy
John D. Kechagias(University of Thessaly), Nikolaos M. Vaxevanidis(School of Pedagogical and Technological Education), Panagiotis G. Asteris(School of Pedagogical and Technological Education), Aristidis Tsiolikas(Technological Educational Institute of Thessaly)
Cited by 17
Related Papers
Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models
|Cement and Concrete Research|2021|668
A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength
|Neural Computing and Applications|2020|456
Concrete compressive strength using artificial neural networks
|Neural Computing and Applications|2019|432
A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model
|Engineering With Computers|2020|349
Mathematical Macromodeling of Infilled Frames: State of the Art
|Journal of Structural Engineering|2011|329