**7. Conclusions**

This article presents an algorithm for constructing an interval pattern recognition procedure. The properties of this algorithm were investigated, and it was shown that with an increase in the dimension of observations, the recognition quality improves:


Therefore, their further development requires assessments of the stability of the results obtained with variations of these critical levels. In addition, an important role in the development of this topic should be played by estimates of the impact of observation errors on the results obtained in the work. If the array of observations of a system consists of parts of its elements' observations, then in the near future, it will be necessary to develop a procedure for comparing the results of processing these parts in order to determine the most sensitive part.

From the author's point of view, this paper is more applied than theoretical. However, to work with the proposed material, it is required to use a more diverse mathematical tool kit than the one that is traditionally used in the listed applications. In particular, when working with mining materials, this allows us to identify economic and safety indicators and significantly reduce the volume of the analyzed information.

The algorithms presented in this paper appeared as a result of long and rather unsuccessful computational experiments. Practice has shown that in order to obtain reasonable applied results, it is necessary to strictly follow the initial meaningful statement of the problem, but the algorithms proposed by the mathematicians themselves should be convenient in calculations and fast enough. Unfortunately, the consumers of these algorithms are often impatient users.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** This paper has no processing of concrete data.

**Conflicts of Interest:** The authors declare no conflict of interest.
