Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
| Published in: | Geoenvironmental Disasters |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1868553883325825025 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Geoenvironmental Disasters |
| description | |
| discipline_display | Environmental Studies |
| discipline_facet | Environmental Studies |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:90530 |
| institution | FRELIP |
| journal_source_facet | Geoenvironmental Disasters |
| last_indexed | 2026-06-20T21:43:55.154Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | A hybrid deep learning model for land subsidence prediction based on TS-InSAR: a case study of Donggugang Environmental Studies General Environmental Studies |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Environmental Studies General Environmental Studies |
| subject_facet | Environmental Studies General Environmental Studies |
| title | A hybrid deep learning model for land subsidence prediction based on TS-InSAR: a case study of Donggugang |
| title_alt | Un modelo híbrido de aprendizaje profundo para la predicción de subsidencia del suelo basado en TS-InSAR: un caso de estudio de Donggugang Un modèle d'apprentissage profond hybride pour la prédiction de l'affaissement des terres basé sur TS-InSAR : une étude de cas de Donggugang Um modelo híbrido de aprendizado profundo para previsão de subsidência do solo baseado em TS-InSAR: um estudo de caso de Donggugang |
| title_auth | A hybrid deep learning model for land subsidence prediction based on TS-InSAR: a case study of Donggugang |
| title_es_txt | Un modelo híbrido de aprendizaje profundo para la predicción de subsidencia del suelo basado en TS-InSAR: un caso de estudio de Donggugang |
| title_fr_txt | Un modèle d'apprentissage profond hybride pour la prédiction de l'affaissement des terres basé sur TS-InSAR : une étude de cas de Donggugang |
| title_full | A hybrid deep learning model for land subsidence prediction based on TS-InSAR: a case study of Donggugang |
| title_fullStr | A hybrid deep learning model for land subsidence prediction based on TS-InSAR: a case study of Donggugang |
| title_full_unstemmed | A hybrid deep learning model for land subsidence prediction based on TS-InSAR: a case study of Donggugang |
| title_pt_txt | Um modelo híbrido de aprendizado profundo para previsão de subsidência do solo baseado em TS-InSAR: um estudo de caso de Donggugang |
| title_short | A hybrid deep learning model for land subsidence prediction based on TS-InSAR: a case study of Donggugang |
| title_sort | a hybrid deep learning model for land subsidence prediction based on ts-insar: a case study of donggugang |
| topic | Environmental Studies General Environmental Studies |
| url | https://link.springer.com/article/10.1186/s40677-026-00391-7 |