Stormwater inflow prediction using radar rainfall data compressed by principal component analysis

K. Katayama, K. Kimijima, O. Yamanaka, A. Nagaiwa & Y. Ono
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 preprocessing radar rainfall data. Then we evaluate the proposed...

2 Related Works

Stormwater inflow prediction using radar rainfall data compressed by principal component analysis

K. Katayama, K. Kimijima, O. Yamanaka, A. Nagaiwa & Y. Ono
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 preprocessing radar rainfall data. Then we evaluate the proposed...

Stormwater inflow prediction using radar rainfall data compressed by principal component analysis

K. Katayama, K. Kimijima, O. Yamanaka, A. Nagaiwa & Y. Ono
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 preprocessing radar rainfall data. Then we evaluate the proposed...

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