Home ›
Entities
› academia
› Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China
Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China
Research article (Journal of Loss Prevention in the Process Industries, 2023) · cited 21× · AI/ML
Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China
Summary
Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China is a scholarly article[1].
Key Facts
Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China'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). Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China. Retrieved May 24, 2026, from https://4ort.xyz/entity/scenario-deduction-of-natech-accident-based-on-dynamic-bayesian-network-a-case-study-of-landslide-accident-in-a-liquor-s
MLA“Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/scenario-deduction-of-natech-accident-based-on-dynamic-bayesian-network-a-case-study-of-landslide-accident-in-a-liquor-s.
BibTeX@misc{4ortxyz_scenario-deduction-of-natech-accident-based-on-dynamic-bayesian-network-a-case-study-of-landslide-accident-in-a-liquor-s_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China}}, year = {2026}, url = {https://4ort.xyz/entity/scenario-deduction-of-natech-accident-based-on-dynamic-bayesian-network-a-case-study-of-landslide-accident-in-a-liquor-s}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China — https://4ort.xyz/entity/scenario-deduction-of-natech-accident-based-on-dynamic-bayesian-network-a-case-study-of-landslide-accident-in-a-liquor-s (retrieved 2026-05-24)
