Investigation of the influence of geographical factors on soil suitability using a nonparametric controlled method of training and data analysis

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: XI International Scientific and Practical Conference Innovative Technologies in Environmental Science and Education (ITSE-2023); Divnomorskoe village, Russia; Divnomorskoe village, Russia

Год издания: 2023

Идентификатор 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 Показать полностьюsignificant 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.

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Издание

Журнал: E3S Web of Conferences

Выпуск журнала: 431

Номера страниц: 03005-03005

Место издания: EDP Sciences

Персоны

  • Gantimurov A.
  • Kravtsov K.
  • Tynchenko V.
  • Evsyukov D.
  • Nelyub V.

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