GAN-technologies in intelligent environments of the subject area

The paper considers the problem of applying GAN-technology in intelligent domain environments (IDEs) for the need to structure large amounts of data and generate initial knowledge. Obtaining new knowledge, which is not explicitly formed by experts, based on available data is an important aspect. The purpose of the study is to determine the features of GAN-technology in IDEs, their close integration with the system of concepts of the subject area expressed in the form of an ontology, the development, use and development of which can be considered as support for the intelligence and development of IDEs as a system. The correlation of cognitive and semantic processes of IDEs is studied to determine the ontological basis of the possibilities of ensuring the evolutionary properties and adaptability of creating the structure and training of neural networks (NN) as NP-complex tasks. The main difference of the study is the cognitive-semantic analysis based on the theory of categories, mathematical logic and universal algebra, relational algebra, namely, the transformation of the ontological dictionary, ontological constructions in open languages of knowledge representation, which makes it possible to apply promising methods based on metaheuristics, the mechanism of which can be represented by a problem-independent high-level algorithmic structure in the form of a set of guiding principles or strategies. GAN-technologies in IDEs are defined as an ontological basis, taking into account the fact that evolutionary properties are taken into account in optimization and adaptability methods. Metaheuristics, based on the metaphor of a natural or artificial process, as the basis for a learning scheme for different groups of features, is an effective basis for solving specific problems of evolutionary origin.