Neural Network Modelling of Flow In Yinluoxia Station Based on Flow in Zhamashike Station in Heihe River, China

DOI

10.2991/aiie-15.2015.58How to use a DOI?

Keywords

artificial neural network; flow; Yinluoxia; Zhamashike; Heihe River

Abstract

Artificial neural network model was established between two river flow in two hydrological stations, Yinluoxia Station and Zhamashike Station in upper Heihe River basin. Results indicate very good correlations for the general trend of the flow data at two stations with correlation coefficients of 0.86 and 0.94 for 2004 and 2005, respectively. Major differences between model results and observations occur near the peak flow or flood periods. This indicates that other factors, such as local rainfalls, can be included in future study to further improve the model accuracy.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - W. Huang
AU  - Y.N. Chao
AU  - S.D. Xu
AU  - Y. Cai
AU  - F. Teng
AU  - B.B. Wang
PY  - 2015/07
DA  - 2015/07
TI  - Neural Network Modelling of Flow In Yinluoxia Station Based on Flow in Zhamashike Station in Heihe River, China
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 206
EP  - 209
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.58
DO  - 10.2991/aiie-15.2015.58
ID  - Huang2015/07
ER  -