Development of machine learning method of titanium alloy properties identification in additive technologies

The Combined Use of the Wiener Polynomial and SVM for Material Classification Task in Medical Implants Production

“…For modeling of the proposed methods, it was used the DataSet from [8,9]. Based on the studies from [8,25], it was possible to distinguish four groups of characteristics that effect a composition of an alloy, which can be synthesized from four different titanium alloys powder components (Fig.…”

“…The need to increase the results accuracy of the materials classification task, cause to the use of effective tools for solving this task. Wiener polynomial (WP), as a universal approximator, can increase the solution accuracy of this task [9]:…”

“…where k is a polynomial degree, 1 ,..., n xx is the variables. This is justified by the Weierstrass first theorem [9]. However, procedures for finding the coefficients of this polynomial by existing methods [20], especially in cases of large dimensional data, are not always effective.…”

“…The problem of developing methods for the effective classification of titanium alloy powders is described in [8,9]. In particular, in [8], a computational intelligence method for determining the optimal microstructure and titanium alloy powders properties is developed.…”

“…In [9] the authors describe a method for the identification of titanium alloys powders based on the use Task in Medical Implants Production Copyright © 2018 MECS I.J. Intelligent Systems and Applications, 2018, 9, 40-47 of a Kolmogorov-Gabor polynomial (Wiener polynomial) and the Random Forest algorithm (RF).…”