Mathematical apparatus of artificial neural networks for genetic algorithm controlling under structural parametric synthesis of large discrete systems.

The article considers the appliance possibility of mathematical apparatus of artificial neural networks for controlling processes of intellectual synthesis of large discrete systems models with a specified behavior. The analysis of the influence of different methods and its classification has carried out, which allows defining the moving trajectory of population in a space of decisions: diffusion to search new extrema and compact study the field in order to increase the speed of population convergence. To solve the problem, using the neural network approach, the two graphical presentations of population conditions have been done: the first, the value of fitness functions of each individual and, the second, some individuals with the same value of adaptation functions. The article defines the structure of the neural network in the form of the network without feed-back and number of neurons in the hidden layer. The training of neural networks has been done and the examples of management decision making based on graphical presentation of the population condition have been provided. The unification of evolutionary procedures by one mathematical apparatus of the Petri net was proposed, which allows using the technology of parallel calculation under programmed realization. Using parallel calculation, combined with proposed models and methods should increase the processing speed of decision-making support systems based on genetic algorithms. [ABSTRACT FROM AUTHOR]