Stacking- and voting-based ensemble deep learning models (SEDL and VEDL) and active learning (AL) for mapping land subsidence-Reference-Cited by-同舟云学术

Stacking- and voting-based ensemble deep learning models (SEDL and VEDL) and active learning (AL) for mapping land subsidence

Published:2022-11-12 Issue:10 Volume:30 Page:26580-26595
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Mohammadifar Aliakbar,Gholami Hamid,Golzari Shahram

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11356-022-24065-7.pdf

Reference45 articles.

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3. Azarakhsh Z, Azadbakht M, Matkan A (2022) Estimation, modeling, and prediction of land subsidence using Sentinel-1 time series in Tehran-Shahriar plain: a machine learning-based investigation. Remote Sens Appl Soc Environ 25:100691

4. Bakr M (2015) Influence of groundwater management on land subsidence in deltas. Water Resour Manage 29(5):1541–1555

5. Breiman L (2001) Random forests. Mach Learn 45(1):5–32

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