dc.contributor.author | Behzadian, Kourosh | |
dc.contributor.author | Ardeshir, Abdollah | |
dc.contributor.author | Kapelan, Zoran | |
dc.contributor.author | Savic, Dragan | |
dc.date.accessioned | 2015-04-29T13:49:09Z | |
dc.date.issued | 2008 | |
dc.description.abstract | A novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (WDS) for the purpose of its hydraulic model calibration is presented. The problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. The objectives are to maximise the calibrated model accuracy and to minimise the number of sampling devices as a surrogate of sampling design cost. Model accuracy is defined as the average of normalised traces of model prediction covariance matrices, each of which is constructed from a randomly generated sample of calibration parameter values. To resolve the computational time issue, the optimisation problem is solved using a multi-objective genetic algorithm and adaptive neural networks (MOGA-ANN). The verification of results is done by comparison of the optimal sampling locations obtained using the MOGA-ANN model to the ones obtained using the Monte Carlo Simulation (MCS) method. In the MCS method, an equivalent deterministic sampling design optimisation problem is solved for a number of randomly generated calibration model parameter samples.The results show that significant computational savings can be achieved by using MOGA-ANN compared to the MCS model or the GA model based on all full fitness evaluations without significant decrease in the final solution accuracy. | en_GB |
dc.identifier.citation | Vol. 6 (1), pp. 48 - 57 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/17054 | |
dc.language.iso | en | en_GB |
dc.publisher | Iran University of Science and Technology (IUST) and Iran Society of Civil Engineers | en_GB |
dc.relation.url | http://ijce.iust.ac.ir/browse.php?a_code=A-10-952-5&slc_lang=en&sid=1 | en_GB |
dc.subject | sampling design | en_GB |
dc.subject | water distribution model | en_GB |
dc.subject | calibration | en_GB |
dc.subject | genetic algorithm | en_GB |
dc.title | Stochastic Sampling Design for Water Distribution Model Calibration | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2015-04-29T13:49:09Z | |
dc.identifier.issn | 1735-0522 | |
dc.description | Copyright © 2008 International Journal of Civil Engineering | en_GB |
dc.identifier.journal | International Journal of Civil Engineering | en_GB |