Forest fire modeling and analysis based on K-means clustering algorithm and time series forecasting-Reference-Cited by-同舟云学术

Forest fire modeling and analysis based on K-means clustering algorithm and time series forecasting

Published:2022-01-21 Issue: Volume: Page:
ISSN:
Container-title:2022 2nd International Conference on Bioinformatics and Intelligent Computing
language:
Short-container-title:

Author:

Li Yuanwei¹,Zhang Sikui¹,Fu Guoyi²

Affiliation:

1. the School of Computer and Network Security(Oxford Brooks College), Chengdu University of Technology, China

2. the School of Mathematical Sciences, Sichuan Normal University, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3523286.3524560

Reference7 articles.

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2. Woodward , C. , & Haines , H. A. ( 2020 ). Unprecedented long-distance transport of macroscopic charcoal from a large, intense forest fire in eastern Australia: Implications for fire history reconstruction. The Holocene, 30(7), 947-952 . Woodward, C., & Haines, H. A. (2020). Unprecedented long-distance transport of macroscopic charcoal from a large, intense forest fire in eastern Australia: Implications for fire history reconstruction. The Holocene, 30(7), 947-952.

3. Zhang , G. , Li , Y. , & Deng , X. ( 2020 ). K-means clustering-based electrical equipment identification for smart building application. Information, 11(1), 2 Zhang, G., Li, Y., & Deng, X. (2020). K-means clustering-based electrical equipment identification for smart building application. Information, 11(1), 2

4. Ahmed , M. , Seraj , R. , & Islam , S. M. S. ( 2020 ). The k-means algorithm: a comprehensive survey and performance evaluation. Electronics, 9(8), 1295 . Ahmed, M., Seraj, R., & Islam, S. M. S. (2020). The k-means algorithm: a comprehensive survey and performance evaluation. Electronics, 9(8), 1295.

5. Parpinelli , R. S. , Lopes , H. S. , & Freitas , A. A. ( 2002 ). An ant colony algorithm for classification rule discovery. In Data mining: A heuristic approach (pp. 191-208). IGI Global . Parpinelli, R. S., Lopes, H. S., & Freitas, A. A. (2002). An ant colony algorithm for classification rule discovery. In Data mining: A heuristic approach (pp. 191-208). IGI Global.

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