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Long-Term Prediction of Discharges in Manwan Reservoir Using Artificial Neural Network Models

  • Conference paper
Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3498))

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Abstract

Several artificial neural network (ANN) models with a feed-forward, back-propagation network structure and various training algorithms, are developed to forecast daily and monthly river flow discharges in Manwan Reservoir. In order to test the applicability of these models, they are compared with a conventional time series flow prediction model. Results indicate that the ANN models provide better accuracy in forecasting river flow than does the auto-regression time series model. In particular, the scaled conjugate gradient algorithm furnishes the highest correlation coefficient and the smallest root mean square error. This ANN model is finally employed in the advanced water resource project of Yunnan Power Group.

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Author information

Authors and Affiliations

  1. Institute of Hydroinformatics, Department of Civil Engineering, Dalian University of Technology, Dalian, Liaoning, 116024, China

    Chuntian Cheng, Yingguang Sun & Jianyi Lin

  2. Department of Civil and Structural Engineering, Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong, China

    Kwokwing Chau

Authors
  1. Chuntian Cheng
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  2. Kwokwing Chau
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  3. Yingguang Sun
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  4. Jianyi Lin
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Cheng, C., Chau, K., Sun, Y., Lin, J. (2005). Long-Term Prediction of Discharges in Manwan Reservoir Using Artificial Neural Network Models. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_165

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  • DOI: https://doi.org/10.1007/11427469_165

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25914-5

  • Online ISBN: 978-3-540-32069-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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