Cite
A Multi-Modal Deep-Learning Air Quality Prediction Method Based on Multi-Station Time-Series Data and Remote-Sensing Images: Case Study of Beijing and Tianjin.
MLA
Xia, Hanzhong, et al. “A Multi-Modal Deep-Learning Air Quality Prediction Method Based on Multi-Station Time-Series Data and Remote-Sensing Images: Case Study of Beijing and Tianjin.” Entropy, vol. 26, no. 1, Jan. 2024, p. 91. EBSCOhost, https://doi.org/10.3390/e26010091.
APA
Xia, H., Chen, X., Wang, Z., Chen, X., & Dong, F. (2024). A Multi-Modal Deep-Learning Air Quality Prediction Method Based on Multi-Station Time-Series Data and Remote-Sensing Images: Case Study of Beijing and Tianjin. Entropy, 26(1), 91. https://doi.org/10.3390/e26010091
Chicago
Xia, Hanzhong, Xiaoxia Chen, Zhen Wang, Xinyi Chen, and Fangyan Dong. 2024. “A Multi-Modal Deep-Learning Air Quality Prediction Method Based on Multi-Station Time-Series Data and Remote-Sensing Images: Case Study of Beijing and Tianjin.” Entropy 26 (1): 91. doi:10.3390/e26010091.