A novel framework of multivariate modeling of water distribution network through 33 factorial design and artificial neural network

Journal of Environmental Science and Health. Part A, Toxic/hazardous Substances & Environmental Engineering
Partha S GhosalDineshwar P Singh

Abstract

The water distribution network is largely affected by the change in the influencing factors, such as input pressure, demand and supply duration. The change in each parameter requires the extensive design of the network and the interactive effect of the influencing parameters are hardly explored. The main hurdles for the water providers lie in the absence of a prediction model, which can be used as a decision tool to assess the effect of the change in parameter and estimating the cost for the changed scenario. The present study developed a novel framework based on the artificial neural network for multivariate prediction modeling taking the response as the cost of the pipe network. The application of the 33 factorial design was used for the selection of the influencing parameters and outcome was taken as the input to the neural network model. The adequacy of the model was tested through error functions and analysis of variance. The low values of the error functions (0.0004-0.228) and high F value (162,442) and R2 (0.999) established the significance of the model. The model can be used for predicting the cost of the changed scenarios and assessment of the optimal solution for the system variables.

References

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Jul 10, 2007·Journal of Environmental Science and Health. Part A, Toxic/hazardous Substances & Environmental Engineering·Min-Young Kim, Min-Kyeong Kim
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Apr 19, 2011·Journal of Environmental Science and Health. Part A, Toxic/hazardous Substances & Environmental Engineering·Yongwen MaHuiping Zhang
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Dec 17, 2015·Environmental Science & Technology·Emily Kumpel, Kara L Nelson
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May 19, 2018·Journal of Environmental Science and Health. Part A, Toxic/hazardous Substances & Environmental Engineering·Erdal Yabalak
Jun 6, 2018·Journal of Environmental Science and Health. Part A, Toxic/hazardous Substances & Environmental Engineering·Partha S Ghosal, Ashok K Gupta

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WaterGEMS
MATLAB
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