Author:
Banda Paul,Bhuiyan Muhammed A.,Hasan Kazi N.,Zhang Kevin,Song Andy
Publisher
Springer International Publishing
Reference23 articles.
1. Ai, S., Chakravorty, A., Rong, C.: Household EV charging demand prediction using machine and ensemble learning. In: 2018 IEEE International Conference on Energy Internet (ICEI), pp. 163–168. IEEE (2018)
2. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)
3. Brownlee, J.: Deep learning for time series forecasting: predict the future with MLPs. CNNs and LSTMs in Python, Machine Learning Mastery (2018)
4. Buzna, L., De Falco, P., Khormali, S., Proto, D., Straka, M.: Electric vehicle load forecasting: A comparison between time series and machine learning approaches. In: 2019 1st International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED), pp. 1–5. IEEE (2019)
5. Fan, C., Sun, Y., Xiao, F., Ma, J., Lee, D., Wang, J., Tseng, Y.C.: Statistical investigations of transfer learning-based methodology for short-term building energy predictions. Appl. Energy 262, 114499 (2020)
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