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Nonparametric System for Automatic Classification of Large-Scale Statistical Data

  • PATTERN RECOGNITION AND IMAGE ANALYSIS AUTOMATED SYSTEMS, HARDWARE AND SOFTWARE
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Abstract

The structure of a nonparametric system for automatic classification of large-scale statistical data is proposed and substantiated. The structure of the system under consideration is made up of a technique for compressing the initial information, algorithms for automatic classification of the transformed data, and a procedure for aggregating the results obtained. To implement the functions of the system under study, new methods are used for testing hypotheses about the distributions of random variables and discretizing the range of their values. The effectiveness of the system is illustrated by the results of its application in assessing the state of forests damaged by the four-eyed fir bark beetle, according to remote sensing data.

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Authors and Affiliations

  1. Institute of Computational Modelling, Siberian Branch of the Russian Academy of Sciences, 660036, Krasnoyarsk, Russian Federation

    A. V. Lapko & V. A. Lapko

  2. Reshetnev Siberian State University of Science and Technology, 660037, Krasnoyarsk, Russian Federation

    A. V. Lapko, V. A. Lapko & V. P. Tuboltsev

Authors
  1. A. V. Lapko
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  2. V. A. Lapko
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  3. V. P. Tuboltsev
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Corresponding authors

Correspondence to A. V. Lapko, V. A. Lapko or V. P. Tuboltsev.

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The authors declare that they have no conflicts of interest.

Additional information

Alexander Vasilievich Lapko. Born in 1949. In 1971 graduated from the Frunze Polytechnic Institute. Doctor of Engineering Sciences since 1990. Works at the Institute of Computational Modelling of the Siberian Branch of the Russian Academy of Sciences as a chief researcher.

Research interests: nonparametric statistics; pattern recognition systems; modeling and optimization of uncertain systems.

Author of 250 scientific articles, including 18 monographs.

Full member of the International Academy of Sciences of Higher Education, member of the editorial board of the scientific journal Computer Science and Control Systems, Honored Worker of Science of the Russian Federation, Honored Worker of Higher Professional Education of the Russian Federation.

Vasily Alexandrovich Lapko. Born in 1974. In 1996 graduated from the Krasnoyarsk State Technical University. Doctor of Engineering Sciences since 2004 in the specialty of System Analysis, Management, and Information Processing. Works at the Institute of Computational Modelling of the Siberian Branch of the Russian Academy of Sciences as a leading researcher. Head of the Department of Space Tools and Technologies of the Reshetnev Siberian State Technical University.

Research interests: nonparametric statistics; pattern recognition systems; modeling of uncertain systems; collective assessment methods.

Author of 205 scientific articles, including eight monographs.

Vitaly Pavlovich Tuboltsev. Born in 1998. In 2022 graduated from the Reshetnev Siberian State University of Science and Technology. Graduate student. Works as an engineer of the first category at the department of remote observations and geoinformation systems of the branch of FBI “RCFH” Centre of Forest Health of Krasnoyarsk oblast, Krasnoyarsk, Russia.

Research interests: development of information tools, nonparametric classification systems, fast decision rule optimization algorithms, remote sensing data processing.

Author of seven scientific articles.

Translated by L. A. Solovyova

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Lapko, A.V., Lapko, V.A. & Tuboltsev, V.P. Nonparametric System for Automatic Classification of Large-Scale Statistical Data. Pattern Recognit. Image Anal. 33, 576–583 (2023). https://doi.org/10.1134/S1054661823030252

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  • DOI: https://doi.org/10.1134/S1054661823030252

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