A comparative study of stochastic and deterministic sampling design for model calibration

Behzadian, Kourosh ORCID: https://orcid.org/0000-0002-1459-8408, Ardeshir, Abdollah, Jalilsani, Fatemeh and Sabour, Farhad (2008) A comparative study of stochastic and deterministic sampling design for model calibration. In: World Environmental and Water Resources Congress 2008, 12-16 May 2008, Honolulu, Hawaii, United States.

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This paper presents and compares two approaches, stochastic and deterministic sampling
design, for the purpose of calibrating water distribution system model. Both approaches
use a multi-objective genetic algorithm known as NSGA-II to identify the whole Paretooptimal
front of optimal solutions. The relevant objective functions are to maximize the
calibrated model accuracy and to minimize the number of sampling devices as a
surrogate of sampling design cost. In the deterministic approach, optimal solutions are
identified based on the assumed values for calibration parameters. However, the
uncertainty of calibration parameters is taken into account in the stochastic approach with
some pre-defined probability density functions. Two different stochastic approaches,
including noisy fitness function and Monte Carlo simulation, are considered in this study.
The efficacy of considering stochastic sampling design rather than deterministic one is
assessed by evaluating their objective functions in the simulation of 10000 sampling
design problems, each of which is constructed with randomly generated calibration
parameters. The stochastic approach is first test on an artificial case study. Then it is
applied to a real world water distribution system known as Mahalat model in the central
part of Iran. The results of comparison show significant improvements in optimal
solutions when using stochastic approaches of sampling design.

Item Type: Conference or Workshop Item (Paper)
Identifier: doi10.1061/40976(316)482
Identifier: doi10.1061/40976(316)482
Keywords: stochastic; deterministic sampling design; model calibration
Subjects: Computing
Construction and engineering
Depositing User: Kourosh Behzadian
Date Deposited: 11 Oct 2023 12:30
Last Modified: 11 Oct 2023 12:30
URI: https://repository.uwl.ac.uk/id/eprint/10189


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