@ARTICLE{Honysz_R._Optimization_2020, author={Honysz, R.}, volume={vol. 65}, number={No 2}, journal={Archives of Metallurgy and Materials}, pages={749-753}, howpublished={online}, year={2020}, publisher={Institute of Metallurgy and Materials Science of Polish Academy of Sciences}, publisher={Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences}, abstract={The article presents a computational model build with the use of artificial neural networks optimized by genetic algorithm. This model was used to research and prediction of the impact of chemical elements and heat treatment conditions on the mechanical properties of ferrite stainless steel. Optimization has allowed the development of artificial neural networks, which showed a better or comparable prediction result in comparison to un-optimized networks has reduced the number of input variables and has accelerated the calculation speed. The introduced computational model can be applied in industry to reduce the manufacturing costs of materials. It can also simplify material selection when an engineer must properly choose the chemical elements and adequate plastic and/or heat treatment of stainless steels with required mechanical properties.}, type={Article}, title={Optimization of Ferrite Stainless Steel Mechanical Properties Prediction with artificial Intelligence Algorithms}, URL={http://czasopisma.pan.pl/Content/116052/PDF/AMM-2020-2-29-Honysz.pdf}, doi={10.24425/amm.2020.132815}, keywords={Analysis and modelling, Numerical Techniques, Computational Material Science, Artificial algorithms, stainless steel}, }