Home ›
Entities
› academia
› Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region
Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region
Research article (Geocarto International, 2021) · cited 54× · AI/ML
Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region
Summary
Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region is a scholarly article[1].
Key Facts
Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid 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). Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-learning-and-boosting-framework-for-piping-erosion-susceptibility-modeling-spatial-evaluation-of-agricultural-areas
MLA“Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-learning-and-boosting-framework-for-piping-erosion-susceptibility-modeling-spatial-evaluation-of-agricultural-areas.
BibTeX@misc{4ortxyz_deep-learning-and-boosting-framework-for-piping-erosion-susceptibility-modeling-spatial-evaluation-of-agricultural-areas_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region}}, year = {2026}, url = {https://4ort.xyz/entity/deep-learning-and-boosting-framework-for-piping-erosion-susceptibility-modeling-spatial-evaluation-of-agricultural-areas}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region — https://4ort.xyz/entity/deep-learning-and-boosting-framework-for-piping-erosion-susceptibility-modeling-spatial-evaluation-of-agricultural-areas (retrieved 2026-05-24)
