Forecasting surface movements based on PSI time series using machine learning algorithms-Reference-Cited by-同舟云学术

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Forecasting surface movements based on PSI time series using machine learning algorithms

Published:2024-03-27 Issue:7 Volume:45 Page:2462-2485
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Yagmur Nur¹^ORCID,Taskin G.²^ORCID,Musaoglu N.³^ORCID,Erten E.³^ORCID

Affiliation:

1. Department of Geomatics Engineering, Engineering Faculty, Gebze Technical University, Kocaeli, Türkiye

2. Institute of Disaster Management, Istanbul Technical University, Istanbul, Türkiye

3. Department of Geomatics Engineering, Civil Engineering Faculty, Istanbul Technical University, Istanbul, Türkiye

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2024.2331977

Reference65 articles.

1. Ground Deformation Pattern Analysis and Evolution Prediction of Shanghai Pudong International Airport Based on PSI Long Time Series Observations

2. Rainfall prediction: A comparative analysis of modern machine learning algorithms for time-series forecasting

3. Monitoring of small-scale deformation at sea-filled Ordu-Giresun Airport, Turkey from multi-temporal SAR data

4. Breiman L. 2001. ST4_Method_Random_Forest Mach. Learn 45(1): 5–32. Department University of California Berkeley. ftp://ftp.stat.berkeley.edu/pub/users/breiman.

5. Soil Moisture Prediction from Remote Sensing Images Coupled with Climate, Soil Texture and Topography via Deep Learning

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