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Use of a supercomputer to advance parameter optimisation using genetic algorithms

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Show simple record Fernando, Achela Jayawardena, Amithirigala 2012-05-27T23:46:39Z 2012-05-27T23:46:39Z 2007-10
dc.identifier.issn 1464-7141
dc.description.abstract Parameter optimisation is a significant but time consuming process that is inherent to conceptual hydrological models representing rainfall-runoff process. This study presents two modifications to achieve optimised results for a Tank Model in less computational time. Firstly, a modified Genetic algorithm (GA) is developed to enhance the fitness of the population consisting of possible solutions in each generation. Then the parallel processing capabilities of an IBM 9076 SP2 Computer is used to expedite implementation of the GA. A comparison of processing time between a serial IBM RS/6000 390 Computer and IBM 9076 SP2 supercomputer reveals that the latter can be up to 8 times faster. The effectiveness of the modified GA is tested with two Tank Models for a hypothetical catchment and a real catchment. The former showed that the parallel GA reaches a lower overall error in reduced time. The overall RMSE expressed as a percentage of actual mean flow rate improves from a 31.8% in a serial processing computer to 29.5% on the SP2 super computer. The case of the real catchment – Shek-Pi-Tau Catchment in Hong Kong – reveals that the supercomputer enhances the swiftness of the GA and achieves objective within a couple of hours. en_NZ
dc.language.iso en en_NZ
dc.publisher IWA Publishing en_NZ
dc.relation.uri en_NZ
dc.rights ©IWA Publishing 2007. The definitive peer-reviewed and edited version of this article is published in Journal of Hydroinformatics 9(4), 319-329, 2007, doi:10.2166/hydro.2007.006, and is available at en_NZ
dc.subject Genetic algorithm en_NZ
dc.subject Tank model en_NZ
dc.subject Parallel processing computers en_NZ
dc.subject Parameter optimisation en_NZ
dc.subject Rainfall-runoff process en_NZ
dc.title Use of a supercomputer to advance parameter optimisation using genetic algorithms en_NZ
dc.type Journal Article en_NZ
dc.rights.holder IWA Publishing en_NZ
dc.identifier.doi 10.2166/hydro.2007.006 en_NZ
dc.subject.marsden 091501 Computational Fluid Dynamics en_NZ
dc.identifier.bibliographicCitation Fernando, A.K., & Jayawardena, A.W. (2007). Use of a supercomputer to advance parameter optimisation using genetic algorithms. Journal of Hydroinformatics, 9(4), 319-329. doi:10.2166/hydro.2007.006 en_NZ
unitec.institution Unitec Institute of Technology en_NZ
unitec.institution University of Hong Kong en_NZ
unitec.publication.spage 319 en_NZ
unitec.publication.lpage 329 en_NZ
unitec.publication.volume 9 en_NZ
unitec.publication.title Journal of Hydroinformatics en_NZ
unitec.peerreviewed yes en_NZ

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