The article considers an effective concept of regression analysis in modeling complex systems and processes. The purpose of the work is to modify the traditional experiment planning strategy, which uses the current information of the next level of experiments. Such a strategy is called a sequential planning experiment or planning active experiments based on regression and variance analyses. The strategy of an active experiment requires the use of a software information product: as information

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... received from the object of study, the strategy of the experiment changes. It is expedient to implement this method in the form of automated systems for processing the results of the experiment. In the future, the method of formalized obtaining the structure of a multifactorial regression model and stable estimation of its coefficient will be used to build high-precision statistical models of the process of growing plants under artificial lighting conditions.