Вани В. Д.
Институт аэрокосмической инженерии, г. Дундигал, р-н Хайдарабад, шт. Телангана, Индия
v.divyavani@iare.ac.in
Радж В. Х.
Факультет прикладных наук Инженерного колледжа «Нью Хорайзон» (New Horizon – «Новый горизонт»), г. Бангалор, шт. Карнатака, Индия
Датт А.
Университет «Лавли Профешинал» (Прекрасный профессиональный университет»), г. Фагвара, шт. Пенджаб, Индия
Равиндранатх Р.
Факультет менеджмента Инженерного колледжа «Мангалам» (Mangalam – «Удача»), г. Коттаям, шт. Керала, Индия
Тьяги Л. К.
Институт менеджмента и технологий «Ллойд» (Lloyd), г. Грейтр-Нойда, шт. Уттар-Прадеш, Индия
Алмусави М.
Факультет инженерии компьютерных технологий Колледжа технической инженерии Исламского университета, г. Наджаф, Ирак
Ядав Д. К.
Институт инженерии и технологий «Ллойд», сектор Ноледж Парк II, г. Грейтр-Нойда, шт. Уттар-Прадеш, Индия
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Предлагаем вниманию читателей немного сокращенный и адаптитрованный перевод доклада преимущественно индийских инженеров-геологиов и геотехников «Подробнее о роли аналитики больших данных в инженерно-геологических изысканиях» (Vani et al., 2024), который был сделан на 3-й Международной конференции по гражданскому строительству, проектированию строительных объектов и инженерным методам охраны окружающей среды (ICS-MEE), проходившей 2–3 мая 2024 года в индийском городе Коттаям штата Керала. Данное мероприятие было организовано Инженерным колледжем «Мангалам», получило финансовую поддержку от Министерства науки и технологий Индии и собрало более 1000 участников со всего мира. Материалы этой конференции были в том же году опубликованы в рецензируемом сборнике трудов научных конференций E3S Web of Conferences, который выпускает французское издательство EDP Sciences (Edition Diffusion Presse Sciences).
DOI: Нет информации
УДК: 624.131; 004
Финансирование: Финансирование
Ссылка для цитирования: Вани В.Д., Радж В.Х., Датт А., Равиндранатх Р., Тьяги Л.К., Алмусави М., Ядав Д.К. Подробнее о роли аналитики больших данных в инженерно-геологических изысканиях (пер. с англ.) // Геоинфо. 2025. Т. 7. № 3. С. 44–53. DOI:10.58339/2949-0677-2025-7-3-44-53
Ключевые слова: инженерная геология; большие данные; искусственный интеллект; машинное обучение
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