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Item Open Access REALIZATION OF ALGORITHM OF SELF-GENERATING NEURAL NETWORKS(Faculty of Engineering and Natural Sciences, 2019) Abdikhaliyev Y.The development of various spheres of human activity is associated with the generation and accumulation of a huge amount of data that can contain the most important practical information. However, significant benefit from this information can be extracted only with proper processing and analysis of this data. Recently, there has been an increased interest in the field of artificial intelligence, and methods of automating the extraction of knowledge based on data mining are actively developing. Self-generating neural networks are built on the principle of biological, of course, with a number of assumptions, they have a huge number of simple processes with many connections. Like the human brain, these networks | are capable of learning. Self-generating neural networks find their application in areas such as computer vision, speech recognition, processing of natural language, etc. The thesis provides an‘analysis of the development of the theory of neural networks, their classification and mathematical formulation of the task of recognizing pattern recognition.Item Open Access Integer Prime Factorization with Deep Learning(Vol 2 No 1 (2021): Advances in Interdisciplinary Sciences, 2021) Murat B.; Kadyrov Sh.; Tabarek R.Prime factor decomposition is a method that is used in number theory and in cryptography, as well. The security of the message depends on the difficulty of factorization. In other words, to hack the RSA system, factorization of N is needed, where N is a product of two prime (generally large) numbers. This paper analyzes the approaches which are already used to solve the problem, and proposes a new method which is expected to increase the efficiency of prime number factorization with the help of neural networks. The results in this paper can be used to develop and improve the security of cryptosystems.