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The convergence of biomaterials and electronic devices provides an intellectual landscape that spans a variety of disciplines including materials science and engineering, physics, chemistry, polymer s...
The material mechanical properties prediction possibility is valuable for manufacturers and design engineers. That is why over one year ago, in [1] modelling results of normalised structural steels m...
Purpose: This paper presents neural network model used for designing the assumed curve of hardness after carbonizing car drive cross in fluidized bed. This process is very complicated and difficult as...
Purpose: The aim of the work is to employ the artificial neural networks for prediction of magnetic saturation of the amorphous alloys with the iron and cobalt matrix. Design/methodology/approach: I...
Purpose: The purpose of this paper is application of neural networks in tribological properties simulation of composite materials based on porous ceramic preforms infiltrated by liquid aluminium allo...
Purpose: The aim of this paper was developing a project of neural network for selection of steel grade with the specified CCT diagram – structure and of harness after heat treatment. Design/methodolo...
Findings: The different heat treatment kinds employed contributed to the improvement of mechanical properties of the alloy with the slight reduction of its plastic properties. Research limitations/im...
Purpose: The goal of this work is to develop the neural network model for prediction of properties Ti+TiN, Ti+Ti(C,N) and Ti+TiC coatings obtained in the PVD process. Design/methodology/approach: Neu...
The neural technique was applied to the analysis of the ultimate tensile strength and additionally the yield strength of austempered ductile iron (ADI). Austempered ductile iron is an excellent materi...

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