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Water Practice & Technology © CSIRO 2006 |
doi10.2166/wpt.2006.017
Stormwater inflow prediction using radar rainfall data compressed by principal component analysis
K. Katayama1, K. Kimijima1, O. Yamanaka1, A. Nagaiwa2, Y. Ono2
1Social Systems R&D Dept., Toshiba Corporation, 1,Toshiba-cho, Fuchu-Shi, Tokyo,
183-8511, Japan
2Electrical & Control Systems engineering Dept. 2, Toshiba Corporation, 1-1, Shibaura
1-Chome, Minato-Ku, Tokyo, 105-8001, Japan
ABSTRACT
This paper proposes a method of stormwater inflow prediction using radar rainfall data as the input of the prediction model constructed by system identification. The aim of the proposal is to construct a compact system by reducing the dimension of the input data. In this paper, Principal Component Analysis (PCA), which is widely used as a statistical method for data analysis and compression, is applied to pre-processing radar rainfall data. Then we evaluate the proposed method using the radar rainfall data and the inflow data acquired in a certain combined sewer system. This study reveals that a few principal components of radar rainfall data can be appropriate as the input variables to storm water inflow prediction model. Consequently, we have established a procedure for the stormwater prediction method using a few principal components of radar rainfall data.
Keywords: principal component analysis; radar rainfall; stormwater inflow prediction; system identification
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