The theoretical foundations for the implementation of the principles of predictive analytics in the class of optimization problems solved in operational processes occurring in drum units are reviewed in the article. A model of the implementation architecture is proposed, and a linear algorithm for solving the optimization problem is developed. The functional significance of linearization at the stage of substantiating goals and objectives in complex technical systems of a closed cycle is indicated. The role of error function minimizing in the operational process of mixture diffusion in drum units is emphasized. Mathematical apparatus of the theory of graphs and methods of dynamic programming has been used to regulate the metric components of the coefficients of the drum units. The values of the optimal machine learning methods for solving of such problems are highlighted. A software algorithm for data generation for control points is proposed. The basis for analysing the instantaneous values of the operation of devices of this type.

Topics
Musical instruments, Machine learning, Optimization problems, Review
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