A novel attention-based LSTM cell post-processor coupled with bayesian optimization for streamflow prediction

Author:

Alizadeh Babak,Ghaderi Bafti Alireza,Kamangir Hamid,Zhang Yu,Wright Daniel B.,Franz Kristie J.

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference87 articles.

1. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., et al., 2016. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467.

2. Multistep-ahead forecasting of coal prices using a hybrid deep learning model;Alameer;Resources Policy,2020

3. Flow alteration by diversion hydropower in tributaries to the salween river: a comparative analysis of two streamflow prediction methodologies;Alipour;International Journal of River Basin Management,2020

4. Alizadeh, B., 2019. Improving post processing of ensemble streamflow forecast for short-to-long ranges: A multiscale approach. Ph.D. thesis.

5. Alizadeh, B., Limon, R.A., Seo, D.J., Lee, H., Brown, J., 2020. A multi-scale post-processing technique for short-to-long range ensemble streamflow prediction. In: 100th American Meteorological Society Annual Meeting, AMS.

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