APA (7th ed.) Citation

X, T., T, M., J, L., W, L., & H, H. (2020). A novel optimized repeatedly random undersampling for selecting negative samples: A case study in an SVM-based forest fire susceptibility assessment. Journal of environmental management, 271, 111014. https://doi.org/10.1016/j.jenvman.2020.111014

Chicago Style (17th ed.) Citation

X, Tang, Machimura T, Li J, Liu W, and Hong H. "A Novel Optimized Repeatedly Random Undersampling for Selecting Negative Samples: A Case Study in an SVM-based Forest Fire Susceptibility Assessment." Journal of Environmental Management 271 (2020): 111014. https://doi.org/10.1016/j.jenvman.2020.111014.

MLA (9th ed.) Citation

X, Tang, et al. "A Novel Optimized Repeatedly Random Undersampling for Selecting Negative Samples: A Case Study in an SVM-based Forest Fire Susceptibility Assessment." Journal of Environmental Management, vol. 271, 2020, p. 111014, https://doi.org/10.1016/j.jenvman.2020.111014.