Article Versions Notes

Pongpiachan S, Wang Q, Apiratikul R, Tipmanee D, Li Y, Xing L, Li G, Han Y, Cao J, Macatangay RC, et al. An Application of Artificial Neural Network to Evaluate the Influence of Weather Conditions on the Variation of PM_2.5-Bound Carbonaceous Compositions and Water-Soluble Ionic Species. Atmosphere. 2022; 13(7):1042. https://doi.org/10.3390/atmos13071042

Pongpiachan, Siwatt, Qiyuan Wang, Ronbanchob Apiratikul, Danai Tipmanee, Yu Li, Li Xing, Guohui Li, Yongming Han, Junji Cao, Ronald C. Macatangay, and et al. 2022. "An Application of Artificial Neural Network to Evaluate the Influence of Weather Conditions on the Variation of PM_2.5-Bound Carbonaceous Compositions and Water-Soluble Ionic Species" Atmosphere 13, no. 7: 1042. https://doi.org/10.3390/atmos13071042

Pongpiachan, S., Wang, Q., Apiratikul, R., Tipmanee, D., Li, Y., Xing, L., Li, G., Han, Y., Cao, J., Macatangay, R. C., Poshyachinda, S., Aekakkararungroj, A., & Hashmi, M. Z. (2022). An Application of Artificial Neural Network to Evaluate the Influence of Weather Conditions on the Variation of PM_2.5-Bound Carbonaceous Compositions and Water-Soluble Ionic Species. Atmosphere, 13(7), 1042. https://doi.org/10.3390/atmos13071042