Applied photogrammetry systems, which act as measuring instruments, are often influenced by the external environment and operating conditions, which determine the accuracy of the results. In this regard, the problem of dynamic adjustment of algorithms for these changing conditions arises. To avoid an increase in the likelihood of human error and to reduce the requirements for personnel qualifications, you can resort to the tools of intelligent systems. For these purposes, the development of appropriate components is required, including machine learning tools. This article proposes a method and procedure for machine learning of the photogrammetric algorithm based on the observation of operator actions and a system of production rules.

Keywords: inductive learning, machine learning, photogrammetry, pattern recognition, photogrammetry, forestry, pipe industry, measurement, mobile app, automation

Due to a significant increase in stress effects on humans at the present time, there is a need to develop methodologies to optimize its functional state. The aim of this study was to search EEG correlates to define the permissible limits of the reserve functional state. The study was used the author's P-adic model of the trajectory transitions psychophysiological States. The study was conducted on 20 male students of the specialty " physical culture Taganrog Institute named after A.P. Chehova sessions free breathing. Removal of biological information produced by the international system "10-20" monopolar scheme on 8 leads (Fp1, Fp2, N3, N4, P3, P4, O1, O2), on the basis of computer EEG system "Kompakt-Neuro" (developer - scientific-medical firm "Neurotech"). These studies showed that paroxysmal activity can act as an EEG correlate of the permissible limits of the reserve functional status, beyond which begin serious pathological processes.

Keywords: electroencephalography, epileptic, the reserves of the organism, altered States of consciousness, extreme conditions.