ПРОГНОЗУВАННЯ МОРОЗНОГО ЗДИМАННЯ ДОРОЖНІХ НАСПІВ: МАШИННЕ НАВЧАННЯ З УРАХУВАННЯМ СКЛАДУ ҐРУНТУ ТА ПОГОДНИХ УМОВ

Yuliia Balashova; Andrii Balashov; Yuliia Balashova; Andrii Balashov

doi:10.30888/2663-5712.2025-33-02-138

Authors

Yuliia Balashova Ukrainian State University of Science and Technologies ESI «Prydniprovska State Academy of Civil Engineering and Architecture» https://orcid.org/0000-0002-2286-9263
Andrii Balashov Ukrainian State University of Science and Technologies ESI «Prydniprovska State Academy of Civil Engineering and Architecture» https://orcid.org/0009-0007-5833-0888

DOI:

https://doi.org/10.30888/2663-5712.2025-33-02-138

Keywords:

frost heave, Support Vector Machines (SVM), cold regions, soil composition, weather data, road embankments, Machine Learning (ML)

Abstract

Frost heave in road embankments is a critical issue in cold-region geotechnical engineering, leading to surface distresses, differential settlements, and maintenance challenges. As climate patterns evolve, accurate frost heave prediction becomes increasin

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