참고문헌
- J. Cao and J, Wang, "Stock price forecasting model based on modified convolution neural network and financial time series analysis," International Journal Communication and Systems, vol. 32, no. 12, article no. e3987, 2019.
- K. Greff, R. K. Srivastava, J. Koutnik, B. R. Steunebrink, and J. Schmidhuber, "LSTM: a search space odyssey," IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 10, pp. 2222-2232, 2016. https://doi.org/10.1109/TNNLS.2016.2582924
- E. W. Saad, D. V. Prokhorov and D. C. Wunsch, "Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks," IEEE Transactions on Neural Networks, vol. 9, no. 6, pp. 1456-1470, 1998. https://doi.org/10.1109/72.728395
- Z. Berradi and M. Lazaar, "Integration of principal component analysis and recurrent neural network to forecast the stock price of Casablanca stock exchange," Procedia Computer Science, vol. 148, pp. 55-61, 2019. https://doi.org/10.1016/j.procs.2019.01.008
- D. L. Minh, A. Sadeghi-Niaraki, H. D. Huy, K. Min, and H. Moon, "Deep learning approach for short-term stock trends prediction based on two-stream gated recurrent unit network," IEEE Access, vol. 6, pp. 55392-55404, 2018. https://doi.org/10.1109/ACCESS.2018.2868970
- Y. Baek and H. Y. Kim, "ModAugNet: a new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module," Expert Systems with Applications, vol. 113, pp. 457-480, 2018. https://doi.org/10.1016/j.eswa.2018.07.019
- D. Bahdanau, K. Cho, and Y. Bengio, "Neural machine translation by jointly learning to align and translate," 2014 [Online]. Available: https://arxiv.org/abs/1409.0473.
- G. Liu and X. Wang, "A numerical-based attention method for stock market prediction with dual information," IEEE Access, vol. 7, pp. 7357-7367, 2019. https://doi.org/10.1109/ACCESS.2018.2886367
- H. Li, Y. Shen, and Y. Zhu. "Stock price prediction using attention-based multi-Input LSTM," in Proceedings of the 10th Asian Conference on Machine Learning, Beijing, China, 2018, pp. 454-469.
- Y. Qin, D. Song, H. Cheng, W. Cheng, G. Jiang, and G. Cottrell, "A dual-stage attention-based recurrent neural network for time series prediction," in Proceedings of the 26th International Joint Conference on Artificial Intelligence, Melbourne, Australia, 2017, pp. 2627-2633.