Využití neurogenetických systémů při podpoře řízení procesu

Abstract

The aim of the thesis is to create an optimal recovery period by using a neurogenetic algorithm. The theoretical part describes in general data mining, neural networks and genetic algorithm. The practical part is focused on describing optimization of maintenance and Weibullov distribution. In the next part of our thesis we solve the problem of determination of parameter m and λ by Weibullov distribution and subsequently comparison of actual and model values of these parameters from Statistica cz. The result is a neurogenetic algorithm impemented in MATLAB software that could be used to support process control.