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Investigation of theinfluence ofgeographical factorson soil suitabilityusing a nonparametriccontrolled method oftraining and dataanalysis Gantimurov A.Kravtsov K.Tynchenko V.2023 год

Investigation of the influence of geographical factors on soil suitability using a nonparametric controlled method of training and data analysis
доклад, тезисы доклада, статья из сборника материалов конференций

Дополнительные ссылки: eLibrary · Источник статьи
База данных: Каталог библиотеки СФУ
Библиографическое описание: Investigation of the influence of geographical factors on soil suitability using a nonparametric controlled method of training and data analysis : доклад, тезисы доклада / A. Gantimurov [et al.]. - [S. l. : s. n.], 2023. - Текст : непосредственный // E3S Web of Conferences : XI International Scientific and Practical Conference Innovative Technologies in Environmental Science and Education (ITSE-2023) / XI International Scientific and Practical Conference Innovative Technologies in Environmental Science and Education (ITSE-2023) (2023 ; 04.09 - 10.09 ; Divnomorskoe village, Russia). - EDP Sciences, 2023. - 431. - P. 03005-03005. - DOI 10.1051/e3sconf/202343103005.
Аннотация: This paper analysed a dataset using a selected data analysis tool. The study found that decision tree was a suitable tool to analyse this data set. Special attention was given to the analysis of geographical factors including an assessment of the presence of water bodies in the county. The analysis showed that these factors have a significant impact on soil workability. Although the model based on these factors did not have absolute accuracy (14% error), it was still acceptable and cheaper to implement. One of the main advantages of using geographical factors to predict soil workability is their easy availability. Data on the presence of water bodies and other geographical indicators can be easily found and used in the analysis. The analysis thus confirms the effectiveness of using decision tree in combination with geographical factors to analyse datasets related to soil serviceability. Despite some inaccuracy of the model, its relative simplicity and accessibility make it an attractive tool for forecasting and decision making in this area.
Год издания: 2023
Авторы: Gantimurov A., Kravtsov K., Tynchenko V., Evsyukov D., Nelyub V.
Издательство: EDP Sciences
Источник: E3S Web of Conferences
Выпуск: 431
Мероприятие: XI International Scientific and Practical Conference Innovative Technologies in Environmental Science and Education (ITSE-2023) (Divnomorskoe village, Russia, 2023 ; 04.09 - 10.09)
Номера страниц: 03005-03005
Количество экземпляров:
Твёрдая копия издания отсутствует в фонде библиотеки

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