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A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China
Research article (Geomatics Natural Hazards and Risk, 2017) · cited 198× · AI/ML
A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China
Summary
A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China is a scholarly article[1].
Key Facts
A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao 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). A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-novel-hybrid-artificial-intelligence-approach-based-on-the-rotation-forest-ensemble-and-naive-bayes-tree-classifiers-f
MLA“A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-novel-hybrid-artificial-intelligence-approach-based-on-the-rotation-forest-ensemble-and-naive-bayes-tree-classifiers-f.
BibTeX@misc{4ortxyz_a-novel-hybrid-artificial-intelligence-approach-based-on-the-rotation-forest-ensemble-and-naive-bayes-tree-classifiers-f_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China}}, year = {2026}, url = {https://4ort.xyz/entity/a-novel-hybrid-artificial-intelligence-approach-based-on-the-rotation-forest-ensemble-and-naive-bayes-tree-classifiers-f}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China — https://4ort.xyz/entity/a-novel-hybrid-artificial-intelligence-approach-based-on-the-rotation-forest-ensemble-and-naive-bayes-tree-classifiers-f (retrieved 2026-05-24)
