Application of Artificial Neural Network to Predict Water Levels in Virginia Key, Florida

DOI

10.2991/aiie-15.2015.57How to use a DOI?

Keywords

artificial neural network; coastal water levels; Cedar Key; Virginia Key; Florida

Abstract

This paper presents the application of the artificial neural network to predict long-term water level in Virginia Key, south Florida. Model input is based on the NOAA observed data at a remote station, Cedar Key station located at about 584 km away. Results indicate that, even though the long distance between two stations, neural network model predictions of water levels are satisfactory, with a 0.86 correlation coefficient. Model accuracy may be further improved by adding more factors, such wind speed and direction, in future studies.

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  - S.D. Xu
AU  - Y.N. Chao
PY  - 2015/07
DA  - 2015/07
TI  - Application of Artificial Neural Network to Predict Water Levels in Virginia Key, Florida
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 203
EP  - 205
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.57
DO  - 10.2991/aiie-15.2015.57
ID  - Huang2015/07
ER  -