Home ›
Entities
› academia
› Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain
Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain
Research article (Progress in Physical Geography Earth and Environment, 2022) · cited 24× · AI/ML
Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain
Summary
Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain is a scholarly article[1].
Key Facts
Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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). Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain. Retrieved May 24, 2026, from https://4ort.xyz/entity/assessing-the-effectiveness-of-alternative-landslide-partitioning-in-machine-learning-methods-for-landslide-prediction-i
MLA“Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/assessing-the-effectiveness-of-alternative-landslide-partitioning-in-machine-learning-methods-for-landslide-prediction-i.
BibTeX@misc{4ortxyz_assessing-the-effectiveness-of-alternative-landslide-partitioning-in-machine-learning-methods-for-landslide-prediction-i_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain}}, year = {2026}, url = {https://4ort.xyz/entity/assessing-the-effectiveness-of-alternative-landslide-partitioning-in-machine-learning-methods-for-landslide-prediction-i}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Assessing the effectiveness of alternative landslide partitioning in machine learning methods for landslide prediction in the complex Himalayan terrain — https://4ort.xyz/entity/assessing-the-effectiveness-of-alternative-landslide-partitioning-in-machine-learning-methods-for-landslide-prediction-i (retrieved 2026-05-24)
