American Psychological Association 6th edition

Sun, K., Zhou, R., Kim, J., & Hu, Y. (2024). Py GRF: An Improved Python Geographical Random Forest Model and Case Studies in Public Health and Natural Disasters. Transactions in GIS, 28(7), 2476-2491. https://doi.org/10.1111/tgis.13248

ISO-690 (author-date, English)

SUN, Kai, ZHOU, Ryan Zhenqi, KIM, Jiyeon and HU, Yingjie, 2024. Py GRF: An Improved Python Geographical Random Forest Model and Case Studies in Public Health and Natural Disasters. Transactions in GIS. 1 November 2024. Vol. 28, no. 7, p. 2476-2491. DOI 10.1111/tgis.13248.

Modern Language Association 9th edition

Sun, K., R. Zhou, J. Kim, and Y. Hu. “Py GRF: An Improved Python Geographical Random Forest Model and Case Studies in Public Health and Natural Disasters.”. Transactions in GIS, vol. 28, no. 7, Nov. 2024, pp. 2476-91, https://doi.org/10.1111/tgis.13248.

Mohr Siebeck - Recht (Deutsch - Österreich)

Sun, Kai/Zhou, Ryan Zhenqi/Kim, Jiyeon/Hu, Yingjie: Py GRF: An Improved Python Geographical Random Forest Model and Case Studies in Public Health and Natural Disasters., Transactions in GIS 2024, 2476-2491.

Emerald - Harvard

Sun, K., Zhou, R., Kim, J. and Hu, Y. (2024), “Py GRF: An Improved Python Geographical Random Forest Model and Case Studies in Public Health and Natural Disasters.”, Transactions in GIS, Vol. 28 No. 7, pp. 2476-2491.

Warning: These citations may not always be 100% accurate.