MULTIOBJECITVE SAMPLING DESIGN FOR CALIBRATION OF WATER DISTRIBUTION NETWORK MODEL USING GENETIC ALGORITHM AND NEURAL NETWORK

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BEHZADIAN K.; ARDESHIR A.A.

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Paper Information

Journal: WATER AND WASTEWATER Year:2008 | Volume:19 | Issue:1 (65) Page(s): 13-22

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Title

MULTIOBJECITVE SAMPLING DESIGN FOR CALIBRATION OF WATER DISTRIBUTION NETWORK MODEL USING GENETIC ALGORITHM AND NEURAL NETWORK

Author(s)

BEHZADIAN K. | ARDESHIR A.A. | Issue Writer Certificate

Keywords

SAMPLING DESIGNQ4

WATER DISTRIBUTION NETWORKQ2

CALIBRATIONQ2

GENETIC ALGORITHMQ2

NEURAL NETWORKQ3

Abstract

In this paper, a novel multiobjective optimization model is presented for selecting optimal locations in the WATER DISTRIBUTION NETWORK (WDN) with the aim of installing pressure loggers. The pressure data collected at optimal locations will be used later on in the CALIBRATION of the proposed WDN model.Objective functions consist of maximization of calibrated model prediction accuracy and minimization of the total cost for SAMPLING DESIGN. In order to decrease the model run time, an optimization model has been developed using multiobjective GENETIC ALGORITHM and adaptive NEURAL NETWORK (MOGAANN).Neural networks (NNs) are initially trained after a number of initial GA generations and periodically retrained and updated after generation of a specified number of full model-analyzed solutions. Trained NNs are replaced with the fitness evaluation of some chromosomes within the GA progress. Using cache prevents objective function evaluation of repetitive chromosomes within GA.Optimal solutions are obtained through pareto-optimal front with respect to the two objective functions. Results show that jointing NNs in MOGA for approximating portions of chromosomes’ fitness in each generation leads to considerable savings in model run time and can be promising for reducing run-time in optimization models with significant computational effort.

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APA: Copy

BEHZADIAN, K., & ARDESHIR, A.A.. (2008). MULTIOBJECITVE SAMPLING DESIGN FOR CALIBRATION OF WATER DISTRIBUTION NETWORK MODEL USING GENETIC ALGORITHM AND NEURAL NETWORK. WATER AND WASTEWATER, 19(1 (65)), 13-22. SID. https://sid.ir/paper/103756/en

Vancouver: Copy

BEHZADIAN K., ARDESHIR A.A.. MULTIOBJECITVE SAMPLING DESIGN FOR CALIBRATION OF WATER DISTRIBUTION NETWORK MODEL USING GENETIC ALGORITHM AND NEURAL NETWORK. WATER AND WASTEWATER[Internet]. 2008;19(1 (65)):13-22. Available from: https://sid.ir/paper/103756/en

IEEE: Copy

K. BEHZADIAN, and A.A. ARDESHIR, “MULTIOBJECITVE SAMPLING DESIGN FOR CALIBRATION OF WATER DISTRIBUTION NETWORK MODEL USING GENETIC ALGORITHM AND NEURAL NETWORK,” WATER AND WASTEWATER, vol. 19, no. 1 (65), pp. 13–22, 2008, [Online]. Available: https://sid.ir/paper/103756/en

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