On the Issue on the Development of Intelligent Decision Support Systems in the Production of Entomophages

Abstract

The work is devoted to the development of intelligent decision support systems in the production of entomophages, using the Bayesian theorem, semantic modeling, data mining; the object of research was management process the cultivation of caterpillars Ephestia kuehniella in a specialized box in the production of entomophage Habrobracon hebetor; identified factors that mainly affect the efficiency of the production of entomophages and the level of quality of entomological products, a Bayesian network in the form of a directed acyclic graph is developed; conditional probabilities for each of the network vertices are defined; the decision-making process on the influence of factors on the efficiency of entomophages production and the level of quality of entomological products in the form of probability distribution diagrams is structured; a predicate semantic network has been developed to formalize the modeling process in the production of entomophages based on the Bayesian theorem; the considered approaches give the chance of formation of optimum strategies of management of manufacture, make decisions on improving production efficiency and level of product quality, using a probabilistic approach.