Forecasting the Efficiency of the Control System of the Technological Object on the Basis of Neural Networks
Nataliia Lutska, Nataliia Zaiets, Lidiia Vlasenko, Vladimir Shtepa, Ольга Вікторівна Савчук
Abstract
Efficient functioning is the first and foremost problem of the control system of technological objects while evaluating its performance. The evaluation criteria can be as follows: the degree of relation between the control action and the control signal; the integrated index of the system dynamics; the statistical measure of the system quality. The article suggests an approach towards forecasting the efficiency of the control system based on neural networks. The efficiency forecasting of the control system on the basis of neural networks with a various number of hidden neurons has been performed. The best result has been demonstrated by the 4-7-2 MLP (multilayer perceptron) network which possesses four input, seven hidden and two output neurons respectively. The MLP has secured 99.19 % performance in the training sample and 98.97 % in the testing sample. The results obtained secure the rational use of the chosen neural network architecture for the purpose of forecasting the efficiency of the control system.