|
|||||
|
|
Identification of the rainfall–runoff relationship in urban drainage networks |
|
| Authors: | Fabio Previdi Marco Lovera Stefano Mambretti |
| Affiliation: | a Dipartimento di Elettronica & Informazione, Politecnico di Milano, Via G. Ponzio, 34/5 – 20133 Milano, Italy b Dipartimento di Ingegneria Idraulica, Ambientale e del Rilevamento, Politecnico di Milano, p.zza Leonardo da Vinci, 32 – 20133 Milano, Italy |
| Abstract: | The calibration of conceptual models for the design of urban drainage networks is an important and well-known problem in hydraulic engineering. In this paper the problem is analysed and the use of black-box identification methods is proposed and applied to experimental data. Both linear (ARX and state space) and nonlinear (polynomial and neural NARX) models are considered and their performance in the simulation and prediction of the network flow from rainfall measurements is evaluated. |
| Keywords: | System identification Urban drainage systems Prediction error methods Subspace methods Nonlinearity tests Polynomial models Neural networks |
| 本文献已被 ScienceDirect 等数据库收录！ | |