Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications

Optimization of Rainfall Sensor Network Layout Based on the Correlation Coefficient Method

Authors
Hongling Zhao, Haibo Yang, Zongmin Wang
Corresponding Author
Hongling Zhao
Available Online January 2016.
DOI
https://doi.org/10.2991/icaita-16.2016.50How to use a DOI?
Keywords
Rainfall sensor network; Correlation coefficient; Rainfall forecast; Spatial correlation style
Abstract
The unreasonable layout of rain sensor networks results in various problems, such as the redundancy of observation nodes, large daily maintenance overhead, and the difficulty of solving faults in real time. A sensor network optimization algorithm based on the correlation coefficient method is proposed in this work. First, Spearman’s rank correlation coefficient is adopted to calculate the correlation of each node, and computing results are stored in databases. Second, the nodes with a significant correlation with other nodes are selected, and historical data are used to verify the selected nodes. Finally, we improve the proposed method by introducing a sub-region calculated using the DEM and growing tree method. Experiment results show that the proposed method can achieve an accurate prediction of rainfall in an entire region with the optimization of the layout of observation nodes.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
Series
Advances in Intelligent Systems Research
Publication Date
January 2016
ISBN
978-94-6252-162-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/icaita-16.2016.50How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Hongling Zhao
AU  - Haibo Yang
AU  - Zongmin Wang
PY  - 2016/01
DA  - 2016/01
TI  - Optimization of Rainfall Sensor Network Layout Based on the Correlation Coefficient Method
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 201
EP  - 205
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.50
DO  - https://doi.org/10.2991/icaita-16.2016.50
ID  - Zhao2016/01
ER  -