Theory and design of an experimental intelligent plant for regulating plant productivity

The article proposes to regulate the values of factors affecting the productivity of plants using an artificial intelligence device, the main element of which is a mathematical neuron. The installation is adaptive to the growing area of the investigated plant object. This increases its efficiency and increases the importance of plant productivity. A block diagram of the experimental setup, a general block diagram of the setup control algorithms have been developed, one of the options for using the experimental setup as a research system for identifying the most significant combinations of factors affecting plant productivity has been considered. To identify the most significant combinations of factors, algorithms based on generalized training algorithms for the Hebb neural network model were used, and a study was made of a model of an installation of four inputs with sigmoidal transfer functions