Using artificial intelligence tools for multi-criteria optimization of the quality tensor

The article describes the development of a methodology for optimizing the quality of the water purification process through the use of digital technologies using tensor calculus, fractional factor planning, statistical modeling, and an artificial neural network. Stages of work: collection of data for the water purification process; building a neural network for each line of the studied process; development and implementation of code to optimize the process. The results of the study can be implemented on a real technological process for water purification.