Optimal Sampling Design for Model Calibration Using Genetic Algorithm: A Case Study

Behzadian, Kourosh ORCID: https://orcid.org/0000-0002-1459-8408, Ardeshir, Abdollah and Sabour, Farhad (2008) Optimal Sampling Design for Model Calibration Using Genetic Algorithm: A Case Study. Amirkabir Journal of Science and Research, 19 (68). pp. 71-79. ISSN 2008-6032

[thumbnail of Behzadian et al 2008.pdf] PDF
Behzadian et al 2008.pdf - Published Version
Restricted to Repository staff only

Download (1MB)

Abstract

Before calibrating a water distribution model, selection of the best points to collect data is undoubtedly an important task for relevant experts. This paper presents a systematic process of sampling design (SD) in a real water distribution network (WDN). The purpose is to find a specific number of optimal monitoring locations in which measurement devices (pressure loggers) will be installed. At first, skeletonization is applied to Mahalat WDN for selecting only the parts of WDN that have significant impact on the behaviour of the system. SD is then formulated and solved as an optimization problem by using a single objective genetic algorithm (SOGA) model. Model prediction accuracy is defined as the objective function. The soloutions obtained by soga are compared to the onest obtained by expert choice (EC). The results show that SOGA can find measurement locations with significantly better predicition accuracy rather than EC.

Item Type: Article
Keywords: Monitoring Location; Calibration; Water Distribution Network; Genetic Algorithm; Expert Choice;
Subjects: Construction and engineering > Civil and environmental engineering
Construction and engineering > Civil and structural engineering
Computing
Construction and engineering
Depositing User: Kourosh Behzadian
Date Deposited: 18 Sep 2023 14:44
Last Modified: 04 Nov 2024 11:36
URI: https://repository.uwl.ac.uk/id/eprint/10231

Actions (login required)

View Item View Item

Menu