A Comparison of One-Class Versus Two-Class Machine Learning Models for Wildfire Prediction in California-Reference-Cited by-同舟云学术

A Comparison of One-Class Versus Two-Class Machine Learning Models for Wildfire Prediction in California

Published:2023-12-05 Issue: Volume: Page:239-253
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
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Author:

Ismail Fathima Nuzla^ORCID,Sengupta Abira^ORCID,Woodford Brendon J.^ORCID,Licorish Sherlock A.^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-8696-5_17

Reference35 articles.

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2. Alkhatib, R., Sahwan, W., Alkhatieb, A., Schütt, B.: A brief review of machine learning algorithms in forest fires science. Appl. Sci. 13(14) (2023). https://doi.org/10.3390/app13148275, https://www.mdpi.com/2076-3417/13/14/8275

3. de Bem, P., de Carvalho Júnior, O., Matricardi, E., Guimarães, R., Gomes, R.: Predicting wildfire vulnerability using logistic regression and artificial neural networks: a case study in Brazil. Int. J. Wildland Fire 28(1), 35–45 (2018). https://doi.org/10.1071/WF18018

4. Bergstra, J., Yamins, D., Cox, D.D.: Making a science of model search: hyperparameter optimization in hundreds of dimensions for vision architectures. In: Proceedings of the 30th International Conference on International Conference on Machine Learning, vol. 28, pp. I-115–I-123. ICML 2013, JMLR.org (2013)

5. Center, N.I.F.: National Wildfire Coordinating Group (NWCG). Interagency Standards for Fire and Fire Aviation Operations. Createspace Independent Publishing Platform, Great Basin Cache Supply Office: Boise, ID, USA (2019)