科研之友
微信
新浪微博
Facebook
分享链接
摘要
The current approaches to the demand calibration of hydraulic models in water distribution system (WDS) are typically slow and not sufficiently reliable. This study introduces "deep fuzzy mapping" (DFM) as the fast and reliable tool for an on-line demand calibration of WDS hydraulic models based on supervisory control and data acquisition. Also, an on-line WDS hydraulic simulation platform is built which consists of a data resource layer, a model processing layer, and an access display layer. The on-line simulation platform is applied to the demo network, and it is verified that a DFM learning algorithm serves as an effective method for the on-line demand calibration of WDS hydraulic model in WDS.
