Super ensemble learning for daily streamflow forecasting: large-scale demonstration and comparison with multiple machine learning algorithms
Sign Up to like & getrecommendations! Published in 2020 at "Neural Computing and Applications"
DOI: 10.1007/s00521-020-05172-3
Abstract: Daily streamflow forecasting through data-driven approaches is traditionally performed using a single machine learning algorithm. Existing applications are mostly restricted to examination of few case studies, not allowing accurate assessment of the predictive performance of… read more here.
Keywords: machine learning; ensemble learning; streamflow forecasting; super ensemble ... See more keywords
Long Term Streamflow Forecasting Using a Hybrid Entropy Model
Sign Up to like & getrecommendations! Published in 2018 at "Water Resources Management"
DOI: 10.1007/s11269-017-1878-0
Abstract: In this paper, the development and evaluation of an entropy based hybrid data driven model coupled with input selection approach and wavelet transformation is investigated for long-term streamflow forecasting with 10 years lead time. To develop… read more here.
Keywords: long term; streamflow forecasting; model; entropy model ... See more keywords
A novel algorithm for feature selection based on geographic distance metric: a case study of streamflow forecasting of Austria’s water resources
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Environmental Science and Technology"
DOI: 10.1007/s13762-019-02485-2
Abstract: This paper focuses on input variable selection—feature selection—methods with the artificial neural network for the streamflow forecasting of large basins that have a variety of numerous stations. The feature selection methods in the current hydrology… read more here.
Keywords: algorithm; feature selection; water; streamflow forecasting ... See more keywords
Ensemble streamflow forecasting based on variational mode decomposition and long short term memory
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DOI: 10.1038/s41598-021-03725-7
Abstract: Reliable and accurate streamflow forecasting plays a vital role in the optimal management of water resources. To improve the stability and accuracy of streamflow forecasting, a hybrid decomposition-ensemble model named VMD-LSTM-GBRT, which is sensitive to… read more here.
Keywords: streamflow forecasting; decomposition; gbrt; mode decomposition ... See more keywords
Comparison of Two Entropy Spectral Analysis Methods for Streamflow Forecasting in Northwest China
Sign Up to like & getrecommendations! Published in 2017 at "Entropy"
DOI: 10.3390/e19110597
Abstract: Monthly streamflow has elements of stochasticity, seasonality, and periodicity. Spectral analysis and time series analysis can, respectively, be employed to characterize the periodical pattern and the stochastic pattern. Both Burg entropy spectral analysis (BESA) and… read more here.
Keywords: entropy spectral; analysis; northwest china; streamflow forecasting ... See more keywords