APPLICATION OF ARTIFICIAL NEURAL NETWORKS TO OPTIMIZE THE CHEMICAL COMPOSITION OF SKI WAXES UNDER DIFFERENT WEATHER CONDITIONS
The paper describes the plan of experimental data collection for training an artificial neural network in the form of a multilayer perceptron to solve the problem of improving the speed performance of skis by finding the best wax composition. The composition of input and output variables of the neural network model that predicts the lubricant composition for a certain combination of weather conditions and piste condition is determined.