Optimizing Anthropometric Characteristics Using Two RBF and Kriging Models

In this research, using anthropometric parameters (input) and functional characteristics (output) of speed of 5, 10 and 20 meters, the top three male wheelchair tennis players of the Islamic Republic of Iran have been studied. Considering that artificial intelligence and machine learning are very important in the field of optimization and parametric study, our goal is to get the best player with the least cost, time and energy using two machine learning algorithms (kriging) and neural network (RBF) and finally reach the best design (player) using genetic algorithm.