The article is devoted to the consideration of topical issues related to the study of the possibility of forecasting the dynamics of stock markets based on neural network models of machine learning. The prospects of applying the neural network approach to building investment forecasts are highlighted. To solve the problem of predicting the dynamics of changes in the value of securities, the problems of training a model on data presented in the form of time series are considered and an approach to the transformation of training data is considered. The method of recursive exclusion of features is described, which is used to identify the most significant parameters that affect price changes in the stock market. An experimental comparison of a number of neural networks was carried out in order to identify the most effective approach to solving the problem of forecasting market dynamics. As a separate example, the implementation of regression based on a radial-basis neural network was considered and an assessment of the quality of the model was presented.
Keywords: stock market, forecast, daily slice, shares, neural network, machine learning, activation function, radial basis function, cross-validation, time series
An auxiliary subsystem of a multi-agent robotic sowing system for agricultural crops, including autonomous robots functioning as part of a group, is considered as an object of research. The aim of the study is to improve the management of adaptability and productivity of agricultural plants. The tasks of the study included the development of the simplest autonomous robot for introducing working fluids into the cenosis and the choice of its parameters. The experimental data were processed by the methods of mathematical statistics. The developed autonomous robot is made of polymer gel and has the properties of a quasi-liquid body. Its parameters are determined, presented experimentally certain mathematical dependences of the interaction of autonomous robots with working fluids, for example, rainwater.
Keywords: seeding, watering, robotic subsystem, autonomous robot, polymer hydrogel, quasi-liquid body