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, software available from tensorflow.org.
2. On the performance of the particle swarm optimization algorithm with various inertia weight variants for computing optimal control of a class of hybrid systems;Arumugam;Discrete Dynamics in Nature and Society,2006
3. Evolutionary and swarm intelligence algorithms;Bansal,2019
4. An evaluation of differential evolution in software test data generation, in: 2009 IEEE Congress on Evolutionary Computation;Becerra;IEEE,2009
5. Evolution strategies–a comprehensive introduction;Beyer;Natural Computing,2002