DocumentCode
532841
Title
Notice of Retraction
Calibration of pipe roughness coefficients under multiple loading conditions by real-coded genetic algorithm
Author
Zhang Weiwei ; Yu Guoping ; Shu Shihu
Author_Institution
Coll. of Environ. Sci. & Eng., Tongji Univ., Shanghai, China
Volume
12
fYear
2010
fDate
22-24 Oct. 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
An implicit mathematical model is developed for calibrating pipe roughness coefficients in water distribution system hydraulic models which takes multiple steady-state loading conditions into account. The calibration model uses real-coded genetic algorithm along with a general network solver to adjust pipe roughness coefficients until simulation results agree with field measurements. An example is presented to show it is able to achieve a good level of accuracy in pipe roughness coefficients and accordingly the model predictions.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
An implicit mathematical model is developed for calibrating pipe roughness coefficients in water distribution system hydraulic models which takes multiple steady-state loading conditions into account. The calibration model uses real-coded genetic algorithm along with a general network solver to adjust pipe roughness coefficients until simulation results agree with field measurements. An example is presented to show it is able to achieve a good level of accuracy in pipe roughness coefficients and accordingly the model predictions.
Keywords
calibration; genetic algorithms; hydraulic systems; mathematical analysis; pipes; water supply; calibration; mathematical model; pipe roughness coefficient; real-coded genetic algorithm; steady-state loading condition; water distribution system hydraulic model; Calibration; Fires; Gallium; Load modeling; Loading; Predictive models; Water resources; calibration; genetic algorithm; hydraulic model; multiple loading conditions; pipe roughness coefficient; water distribution system;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Type
conf
DOI
10.1109/ICCASM.2010.5622414
Filename
5622414
Link To Document