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You are here : eLibrary : IAHR World Congress Proceedings : 34th Congress - Brisbane (2011) : THEME 1: Extremes and Variability : Optimal parameter estimation of a new rapid flood spreading model using multi-objectives
Optimal parameter estimation of a new rapid flood spreading model using multi-objectives
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In order to successfully calibrate a numerical model, multiple criteria should be considered. Multi-objective Differential Evolution (MODE) and Multi-objective Particle Swarm Optimisation (MOPSO) have proved effective in numerous such applications, where most of the techniques relying on the condition of Pareto efficiency to compare different solutions. We describe the performance of two population based search algorithms (Nondominated Sorting Particle Swarm Optimisation (NSPSO), and Nondominated Sorting Differential Evolution (NSDE)) when applied to calibration of a rapid flood spreading model (RFSM). Formulation of an automatic calibration strategy for the RFSM is outline. The simulations show that the both methods possess the ability to find the optimal Pareto front.
File Size : 321,554 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 34th Congress - Brisbane (2011)
Article : THEME 1: Extremes and Variability
Date Published : 07/08/2012
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