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Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China
Research article (Sensors, 2022) · cited 20× · AI/ML
Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China
Summary
Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China is a scholarly article[1].
Key Facts
Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China. Retrieved May 24, 2026, from https://4ort.xyz/entity/combined-sbas-insar-and-pso-rf-algorithm-for-evaluating-the-susceptibility-prediction-of-landslide-in-complex-mountainou
MLA“Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/combined-sbas-insar-and-pso-rf-algorithm-for-evaluating-the-susceptibility-prediction-of-landslide-in-complex-mountainou.
BibTeX@misc{4ortxyz_combined-sbas-insar-and-pso-rf-algorithm-for-evaluating-the-susceptibility-prediction-of-landslide-in-complex-mountainou_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China}}, year = {2026}, url = {https://4ort.xyz/entity/combined-sbas-insar-and-pso-rf-algorithm-for-evaluating-the-susceptibility-prediction-of-landslide-in-complex-mountainou}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China — https://4ort.xyz/entity/combined-sbas-insar-and-pso-rf-algorithm-for-evaluating-the-susceptibility-prediction-of-landslide-in-complex-mountainou (retrieved 2026-05-24)
