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An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems

Publication ,  Journal Article
de Faria, VAD; de Queiroz, AR; Lima, LM; Lima, JWM; da Silva, BC
Published in: International Journal of Environmental Science and Technology
July 1, 2022

This work analyzes the use of artificial neural networks in the short-term streamflow forecasting for large interconnected hydropower systems. The state-of-the-art optimization algorithms, activation functions, and weight initialization techniques are investigated together with classic methods. We present an algorithm to define the neural network inputs in large hydrosystems and apply it to create models for 55 major hydro plants located in the Paraná Basin, which contribute to more than 30% of the total power generated in Brazil. The paper also compares the performance of the neural networks with the hydrological models that are currently used by the independent system operator to define the dispatch of the electric power generators. Our results show that, overall, the neural network models provide more accurate forecasts than the hydrological models used by the Brazilian System Operator. Finally, the paper discusses the contributions of historical rainfall information in the forecasting of streamflow while using neural network models.

Duke Scholars

Published In

International Journal of Environmental Science and Technology

DOI

EISSN

1735-2630

ISSN

1735-1472

Publication Date

July 1, 2022

Volume

19

Issue

7

Start / End Page

5819 / 5838

Related Subject Headings

  • Environmental Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
de Faria, V. A. D., de Queiroz, A. R., Lima, L. M., Lima, J. W. M., & da Silva, B. C. (2022). An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems. International Journal of Environmental Science and Technology, 19(7), 5819–5838. https://doi.org/10.1007/s13762-021-03565-y
Faria, V. A. D. de, A. R. de Queiroz, L. M. Lima, J. W. M. Lima, and B. C. da Silva. “An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems.” International Journal of Environmental Science and Technology 19, no. 7 (July 1, 2022): 5819–38. https://doi.org/10.1007/s13762-021-03565-y.
de Faria VAD, de Queiroz AR, Lima LM, Lima JWM, da Silva BC. An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems. International Journal of Environmental Science and Technology. 2022 Jul 1;19(7):5819–38.
de Faria, V. A. D., et al. “An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems.” International Journal of Environmental Science and Technology, vol. 19, no. 7, July 2022, pp. 5819–38. Scopus, doi:10.1007/s13762-021-03565-y.
de Faria VAD, de Queiroz AR, Lima LM, Lima JWM, da Silva BC. An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems. International Journal of Environmental Science and Technology. 2022 Jul 1;19(7):5819–5838.
Journal cover image

Published In

International Journal of Environmental Science and Technology

DOI

EISSN

1735-2630

ISSN

1735-1472

Publication Date

July 1, 2022

Volume

19

Issue

7

Start / End Page

5819 / 5838

Related Subject Headings

  • Environmental Sciences