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Comprehensive Building Fire Risk Prediction Using Machine Learning and Stacking Ensemble Methods

Research article (Fire, 2024) · cited 13× · AI/ML
academia openalex:W4402824608
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Comprehensive Building Fire Risk Prediction Using Machine Learning and Stacking Ensemble Methods

Summary

Comprehensive Building Fire Risk Prediction Using Machine Learning and Stacking Ensemble Methods is a scholarly article[1].

Key Facts

  • Comprehensive Building Fire Risk Prediction Using Machine Learning and Stacking Ensemble Methods's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Comprehensive Building Fire Risk Prediction Using Machine Learning and Stacking Ensemble Methods. Retrieved May 24, 2026, from https://4ort.xyz/entity/comprehensive-building-fire-risk-prediction-using-machine-learning-and-stacking-ensemble-methods
MLA “Comprehensive Building Fire Risk Prediction Using Machine Learning and Stacking Ensemble Methods.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/comprehensive-building-fire-risk-prediction-using-machine-learning-and-stacking-ensemble-methods.
BibTeX @misc{4ortxyz_comprehensive-building-fire-risk-prediction-using-machine-learning-and-stacking-ensemble-methods_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Comprehensive Building Fire Risk Prediction Using Machine Learning and Stacking Ensemble Methods}}, year = {2026}, url = {https://4ort.xyz/entity/comprehensive-building-fire-risk-prediction-using-machine-learning-and-stacking-ensemble-methods}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Comprehensive Building Fire Risk Prediction Using Machine Learning and Stacking Ensemble Methods — https://4ort.xyz/entity/comprehensive-building-fire-risk-prediction-using-machine-learning-and-stacking-ensemble-methods (retrieved 2026-05-24)

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