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- W2249156724 abstract "Modeling the rainfall-runoff process is always a difficult task in simulation of the whole hydrological cycle. For the purpose of simplifying calculation and enhancing the adaptability, neural networks have been extensively applied to hydrological modeling recently. In this study, a modified state space neural network (MSSNN) was proposed to improve the structures of neural network and to realize the transition of unit hydrograph from the weights of MSSNN. We used a two-step procedure to design the structure of MSSNN and to determine the weights of MSSNN. In simulation of the rainfall-runoff process by MSSNN, we adopted a dynamical gradient descent learning algorithm to update the weights in every time step. As a result, the transition of unit hydrograph was obtained based on the changes of the weights of MSSNN." @default.
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- W2249156724 date "2002-01-01" @default.
- W2249156724 modified "2023-09-24" @default.
- W2249156724 title "A Modified State Space Neural Network Model to Derive a Unit Hydrograph" @default.
- W2249156724 hasPublicationYear "2002" @default.
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