Application of feed-forward and recurrent neural network in modelling the adsorption of boron by amidoxime-modified poly(Acrylonitrile-co-Acrylic Acid).

MLA

Kia Li, Lau, et al. “Application of Feed-Forward and Recurrent Neural Network in Modelling the Adsorption of Boron by Amidoxime-Modified Poly(Acrylonitrile-Co-Acrylic Acid).” Environmental Engineering Research, vol. 25, no. 6, Dec. 2020, pp. 830–40. EBSCOhost, https://doi.org/10.4491/eer.2019.138.

APA

Kia Li, L., Jamil, S. N. A. M., Abdullah, L. C., Ibrahim, N. N. L. N., Adekanmi, A. A., & Nourouzi, M. (2020). Application of feed-forward and recurrent neural network in modelling the adsorption of boron by amidoxime-modified poly(Acrylonitrile-co-Acrylic Acid). Environmental Engineering Research, 25(6), 830–840. https://doi.org/10.4491/eer.2019.138

Chicago

Kia Li, Lau, Siti Nurul Ain Md. Jamil, Luqman Chuah Abdullah, Nik Nor Liyana Nik Ibrahim, Adeyi Abel Adekanmi, and Mohsen Nourouzi. 2020. “Application of Feed-Forward and Recurrent Neural Network in Modelling the Adsorption of Boron by Amidoxime-Modified Poly(Acrylonitrile-Co-Acrylic Acid).” Environmental Engineering Research 25 (6): 830–40. doi:10.4491/eer.2019.138.