Home ›
Entities
› academia
› Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region
Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region
Research article (Stochastic Environmental Research and Risk Assessment, 2022) · cited 48× · AI/ML
Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region
Summary
Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region is a scholarly article[1].
Key Facts
Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region'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). Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region. Retrieved May 24, 2026, from https://4ort.xyz/entity/prediction-of-spatial-landslide-susceptibility-applying-the-novel-ensembles-of-cnn-glm-and-random-forest-in-the-indian-h
MLA“Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/prediction-of-spatial-landslide-susceptibility-applying-the-novel-ensembles-of-cnn-glm-and-random-forest-in-the-indian-h.
BibTeX@misc{4ortxyz_prediction-of-spatial-landslide-susceptibility-applying-the-novel-ensembles-of-cnn-glm-and-random-forest-in-the-indian-h_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region}}, year = {2026}, url = {https://4ort.xyz/entity/prediction-of-spatial-landslide-susceptibility-applying-the-novel-ensembles-of-cnn-glm-and-random-forest-in-the-indian-h}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region — https://4ort.xyz/entity/prediction-of-spatial-landslide-susceptibility-applying-the-novel-ensembles-of-cnn-glm-and-random-forest-in-the-indian-h (retrieved 2026-05-24)
