Indicators and Algorithms for Assessing the Identification Results Quality of the Adjacent Territories State

Machine learning methods for identification of territories near railway infrastructure facilities are considered. The main sources of initial data are presented, as well as algorithms for assessing the quality of the results for landscape elements automated identification using the forest vegetation example. Forest vegetation state identification is carried out based on spectral-brightness characteristics determined using multispectral aerospace imaging materials. Quality indicators for the results of survey materials automated processing and algorithms for calculating the considered indicators are proposed. Examples are given to assess the results quality of using machine learning methods.

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Publication Details

Journal
Intellectual Technologies on Transport
Published
2024-10-09
DOI
https://doi.org/10.20295/2413-2527-2024-339-73-82
Primary Topic
Economic and Technological Developments in Russia
Type
article
Field-Weighted Citation Impact
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article

Indicators and Algorithms for Assessing the Identification Results Quality of the Adjacent Territories State

Vyacheslav Zelencov, Виктор Мочалов
Intellectual Technologies on Transport
Economic and Technological Developments in Russia
article

Indicators and Algorithms for Assessing the Identification Results Quality of the Adjacent Territories State

Vyacheslav Zelencov, Виктор Мочалов
article en

Abstract

Machine learning methods for identification of territories near railway infrastructure facilities are considered. The main sources of initial data are presented, as well as algorithms for assessing the quality of the results for landscape elements automated identification using the forest vegetation example. Forest vegetation state identification is carried out based on spectral-brightness characteristics determined using multispectral aerospace imaging materials. Quality indicators for the results of survey materials automated processing and algorithms for calculating the considered indicators are proposed. Examples are given to assess the results quality of using machine learning methods.

Intellectual Technologies on TransportVol. 0(3)
Russian Academy of Sciences (RU), Military Space Academy named after AF Mozhaisky (RU), State Research Center of the Russian Federation (RU)
Industry, innovation and infrastructure
Openalex Percentile: Top 64%
Economic and Technological Developments in Russia
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Indicators and Algorithms for Assessing the Identification Results Quality of the Adjacent Territories State — Vyacheslav Zelencov, Виктор Мочалов · Intellectual Technologies on Transport (2024) | TGRS Research Map | TGRS