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Article

Sensitivity Analysis for Performance Evaluation of a Real Water Distribution System by a Pressure Driven Analysis Approach and Artificial Intelligence Method

1
Department of Civil Engineering, University of Calabria, 87036 Arcavacata, Italy
2
Korea Water Resources Corporation (K-Water), Daejeon 34045, Korea
3
Department of Energy IT, Gachon University, Seongnam 13120, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Dimitri P. Solomatine
Water 2021, 13(8), 1116; https://doi.org/10.3390/w13081116
Received: 27 December 2020 / Revised: 22 March 2021 / Accepted: 15 April 2021 / Published: 18 April 2021
Proper performance of water distribution networks (WDNs) plays a vital role in customer satisfaction. The aim of this study is to conduct a sensitivity analysis to evaluate the behavior of WDNs analyzed by a pressure-driven analysis (PDA) approach and the classification technique by using an appropriate artificial neural network, namely the Group Method of Data Handling (GMDH). For this purpose, this study is divided into four distinct steps. In the first and second steps, a real network has been analyzed by using a Pressure-Driven Analysis approach (PDA) to obtain the pressure, and α coefficient, the percentage of supplied flow. The analysis has been performed by using three different values of the design peak coefficient k*. In the third step, the Group Method of Data Handling (GMDH) has been applied and several binary models have been constructed. The analysis has been carried out by using input data, including the real topology of the network and the base demand necessary to satisfy requests of users in average conditions and by assuming that the demand in each single one-hour time step depends on a peak coefficient. Finally, the results obtained from the PDA hydraulic analysis and those obtained by using them in the GMDH algorithm have been compared and sensitivity analysis has been carried out. The innovation of the study is to demonstrate that the input parameters adopted in the design are correct. The analysis confirms that the GMDH algorithm gives proper results for this case study and the results are stable also when the value of each k*, characteristic of a different time hour step, varies in an admissible technical range. It was confirmed that the results obtained by using the PDA approach, analyzed by using a GMDH-type neural network, can provide higher performance sufficiency in the evaluation of WDNs. View Full-Text
Keywords: water distribution networks; PDA; sensitivity analysis; GMDH algorithm; artificial neural network; binary model water distribution networks; PDA; sensitivity analysis; GMDH algorithm; artificial neural network; binary model
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MDPI and ACS Style

Fiorini Morosini, A.; Shaffiee Haghshenas, S.; Shaffiee Haghshenas, S.; Choi, D.Y.; Geem, Z.W. Sensitivity Analysis for Performance Evaluation of a Real Water Distribution System by a Pressure Driven Analysis Approach and Artificial Intelligence Method. Water 2021, 13, 1116. https://doi.org/10.3390/w13081116

AMA Style

Fiorini Morosini A, Shaffiee Haghshenas S, Shaffiee Haghshenas S, Choi DY, Geem ZW. Sensitivity Analysis for Performance Evaluation of a Real Water Distribution System by a Pressure Driven Analysis Approach and Artificial Intelligence Method. Water. 2021; 13(8):1116. https://doi.org/10.3390/w13081116

Chicago/Turabian Style

Fiorini Morosini, Attilio; Shaffiee Haghshenas, Sina; Shaffiee Haghshenas, Sami; Choi, Doo Y.; Geem, Zong W. 2021. "Sensitivity Analysis for Performance Evaluation of a Real Water Distribution System by a Pressure Driven Analysis Approach and Artificial Intelligence Method" Water 13, no. 8: 1116. https://doi.org/10.3390/w13081116

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