An interpretable hybrid deep learning model for flood forecasting based on Transformer and LSTM

Author:

Li Wenzhong,Liu Chengshuai,Xu Yingying,Niu Chaojie,Li Runxi,Li Ming,Hu Caihong,Tian Lu

Publisher

Elsevier BV

Reference64 articles.

1. Peeking inside the black-box: a survey on explainable artificial intelligence (XAI);Adadi;IEEE Access,2018

2. Bahdanau, D., Cho, K., Bengio, Y., 2016. Neural Machine Translation by Jointly Learning to Align and Translate. https://doi.org/10.48550/arXiv.1409.0473.

3. Explainable artificial intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI;Barredo Arrieta;Inf. Fusion,2020

4. Bergstra, J., Bengio, Y., 2012. Random search for hyper-parameter optimization. The Journal of Machine Learning Research.

5. Di Nunno, F. 1, de Marinis, G. 1, Granata, F. 1 1 U. of C., Southern Lazio, D. of C., Mechanical Engineering (DICEM), F., 2023. Short-term forecasts of streamflow in the UK based on a novel hybrid artificial intelligence algorithm 7036. https://doi.org/10.1038/s41598-023-34316-3.

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