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An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China
Research article (Natural Hazards, 2021) · cited 21× · AI/ML
An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China
Summary
An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China is a scholarly article[1].
Key Facts
An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, 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). An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-ensemble-risk-assessment-model-for-urban-rainstorm-disasters-based-on-random-forest-and-deep-belief-nets-a-case-study
MLA“An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-ensemble-risk-assessment-model-for-urban-rainstorm-disasters-based-on-random-forest-and-deep-belief-nets-a-case-study.
BibTeX@misc{4ortxyz_an-ensemble-risk-assessment-model-for-urban-rainstorm-disasters-based-on-random-forest-and-deep-belief-nets-a-case-study_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China}}, year = {2026}, url = {https://4ort.xyz/entity/an-ensemble-risk-assessment-model-for-urban-rainstorm-disasters-based-on-random-forest-and-deep-belief-nets-a-case-study}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An ensemble risk assessment model for urban rainstorm disasters based on random forest and deep belief nets: a case study of Nanjing, China — https://4ort.xyz/entity/an-ensemble-risk-assessment-model-for-urban-rainstorm-disasters-based-on-random-forest-and-deep-belief-nets-a-case-study (retrieved 2026-05-24)
