Assessment of urban ground collapse susceptibility based on RF-BP neural network coupling model: A case study of typical areas in Hangzhou City

To improve the current situation where ground subsidence susceptibility assessment mainly relies on knowledge-driven models, this study explores the feasibility of incorporating data-driven models into the evaluation of urban ground subsidence. The study focused on a typical area in Hangzhou charact...

Бүрэн тодорхойлолт

Номзүйн дэлгэрэнгүй

Үндсэн зохиолчид:	Bofan YU, Huaixue XING, Liling ZHOU, Jiaxing YAN, Jinrui ZHANG, Meijun XU
Формат:	Artigo
Хэл сонгох:	Chinês
Хэвлэсэн:	Editorial Office of The Chinese Journal of Geological Hazard and Control 2025-06-01
Цуврал:	Zhongguo dizhi zaihai yu fangzhi xuebao
Нөхцлүүд:	ground collapse disaster susceptibility assessment machine learning model selection of evaluation factors
Онлайн хандалт:	https://www.zgdzzhyfzxb.com/en/article/doi/10.16031/j.cnki.issn.1003-8035.202311017
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!