In this work an analysis of neurocontrollers is given. The purpose of this paper is the neurocontroler for attitude control: satellite rotations. The classification of neurocontroller architecture is provided. The pros and cons of different neurocontrollers are described. Two configuration of neural networkfeedforward neural networks with mini-batch descent and modified Elman neural network, are investigated in this work to verify its ability to control the attitude of a satellite. The advantages and disadvantage of different predictive model neurorization systems are described. The class diagram for the simulating of satellite rotation for neural network learning is given. The proposed approach provides the architecture of the neural network and the weights among the layers in order to guarantee stability of the system. The accuracy was calculated. The AI module, after trained for different configurations of wheels, will get commands with desired 3D rotation speeds and control the wheels to achieve the desired rotation speeds.

The paper examines the efficiency of the application of CUDA technologies for the parallelization of the cryptographic algorithm with the public key. The speed of execution of several implementations of the algorithm is compared: sequential implementation on the CPU and two parallel implementations – on the CPU and GPU. A description of the public key algorithm is presented, as well as properties that allow it to be parallelized. The advantages and disadvantages of parallel implementations are analyzed. It is shown that each of them can be suitable for different scenarios. The software was developed and several numerical experiments were performed. The reliability of the obtained results of encryption and decryption is confirmed. To eliminate the influence of external factors at the time of execution the algorithm was tested ten times in a row and the average value was calculated. Acceleration coefficients for message encryption and decryption algorithms were estimated based on OpenMP and CUDA technology. The proposed approach focuses on the possibility of further optimization through the prospects of developing a multi-core architecture of computer systems and graphic processors.

The method of vitality of the information product evaluation is built. This method, as opposed to others, takes into account components of the information product, which gave an opportunity to forecast (predict) the sequence of changes in its states. The operations over the relation with indeterminacy for the purpose of their application in the data warehouse with the consolidated data are improved that allowed realizing unary operations of Big data catalogue.The method for reducing the indeterminacy of data available in the repository of consolidated data as a basis for further evaluation of the quality of consolidated data was created. The considered methods are useful also for decision making, because they provide a search for hidden relationships between the characteristics of the consolidated data repository. Such dependence should be considered when making decisions based on consolidated data.The result of this work is to reduce the uncertainty for assessing the viability of the information product. This allows us to increase the quality of the information product for Big data analysis.

The new technology for Industry 4.0 implementation is proposed. This technology is implemented in one of Ukrainian manufacture. The equipment identification module on the workstation is provided accounting and quality analysis of equipment. The module of the interface part of human-machine interaction during the maintenance of all parts of the production process of the press-shop is developed. The main stages of development and results evaluation is described. The key performance indicators for project management is given.