COMPUTER MODELS OF ARTIFICIAL INTELLIGENCE SYSTEMS BASED ON NEURAL NETWORKS

The possibilities of artificial neural networks as a basis for creating artificial intelligence systems are considered. The main advantage of artificial neural networks is their ability to learn, generalize, and identify hidden dependencies in the source data. The peculiarities, classification, and methods of training artificial neural networks and the tasks successfully solved using these networks are presented. The stages of solving various problems using artificial neural networks are considered. The features of fuzzy neural networks, deep neural networks, and convolutional neural networks are considered in detail. The following examples of intelligent systems developed on the basis of artificial neural networks are considered: a system for approximating functions from noisy data, a system for classifying large amounts of data, an automatic control system, a cryptographic system, and an image recognition system. Computer models of these systems have been developed, implemented as computer programs. The results of the work of the considered intelligent systems are presented in a visual graphical form.