Author:
Hadjout D.,Torres J. F.,Sebaa A.,Martínez-Álvarez F.
Publisher
Springer International Publishing
Reference19 articles.
1. Cho, H., Kim, Y., Lee, E., Choi, D., Lee, Y., Rhee, W.: Basic enhancement strategies when using Bayesian optimization for hyperparameter tuning of deep neural networks. IEEE Access 8, 52588–52608 (2020)
2. Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. In: Proceedings of the NIPS 2014 Workshop on Deep Learning, pp. 1–9 (2014)
3. Divina, F., Torres, J.F., García-Torres, M., Martínez-Álvarez, F., Troncoso, A.: Hybridizing deep learning and neuroevolution: application to the Spanish short-term electric energy consumption forecasting. Appl. Sci. 10(16), 5487 (2020)
4. Fahiman, F., Erfani, S.M., Rajasegarar, S., Palaniswami, M., Leckie, C.: Improving load forecasting based on deep learning and K-Shape clustering. In: Proceedings of the International Joint Conference on Neural Networks, pp. 4134–4141 (2017)
5. Gutiérrez-Avilés, D., et al.: SmartFD: a real big data application for electrical fraud detection. In: de Cos Juez, F., et al. (eds.) Hybrid Artificial Intelligent Systems. HAIS 2018. Lecture Notes in Computer Science, vol. 10870, pp. 120–130. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92639-1_11
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