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Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii
Research article (Expert Systems with Applications, 2024) · cited 23× · AI/ML
Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii
Summary
Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii is a scholarly article[1].
Key Facts
Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii'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). Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii. Retrieved May 24, 2026, from https://4ort.xyz/entity/advancing-the-lightgbm-approach-with-three-novel-nature-inspired-optimizers-for-predicting-wildfire-susceptibility-in-ka
MLA“Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/advancing-the-lightgbm-approach-with-three-novel-nature-inspired-optimizers-for-predicting-wildfire-susceptibility-in-ka.
BibTeX@misc{4ortxyz_advancing-the-lightgbm-approach-with-three-novel-nature-inspired-optimizers-for-predicting-wildfire-susceptibility-in-ka_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii}}, year = {2026}, url = {https://4ort.xyz/entity/advancing-the-lightgbm-approach-with-three-novel-nature-inspired-optimizers-for-predicting-wildfire-susceptibility-in-ka}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii — https://4ort.xyz/entity/advancing-the-lightgbm-approach-with-three-novel-nature-inspired-optimizers-for-predicting-wildfire-susceptibility-in-ka (retrieved 2026-05-24)
