1. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X., 2015.TensorFlow: Large-scale machine learning on heterogeneous systems.〈https://www.tensorflow.org/〉.software available from tensorflow.org.
2. Introduction to Numerical Methods in Chemical Engineering;Ahuja,2019
3. Ann for hybrid modelling of batch and fed-batch chemical reactors;Ammar;Chem. Eng. Sci.,2021
4. Efficiente Learning Machines Theories, Concepts, and Applications for Engineers and System Designers;Awad,2015
5. Dynamic optimization of dry reformer under catalyst sintering using neural networks;Azzam;Energy Convers. Manag.,2018