کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
387004 660893 2009 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatic calibration of a rainfall–runoff model using a fast and elitist multi-objective particle swarm algorithm
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Automatic calibration of a rainfall–runoff model using a fast and elitist multi-objective particle swarm algorithm
چکیده انگلیسی

In order to successfully calibrate a numerical model, multiple criteria should be considered. Multi-objective genetic algorithms (MOGAs) have proved effective in numerous such applications, where most of the techniques relying on the condition of Pareto efficiency to compare different solutions. In this paper, a new non-dominated sorting particle swarm optimisation (NSPSO), is proposed, that combines the operations (fast ranking of non-dominated solutions, crowding distance ranking and elitist strategy of combining parent population and offspring population together) of a known MOGA NSGA-II and the other advanced operations (selection and mutation operations) with a single particle swarm optimisation (PSO). The efficacy of this algorithm is demonstrated on the calibration of a rainfall–runoff model, and the comparison is made with the NSGA-II. The simulation results suggest that the proposed optimisation framework is able to achieve good solutions as well diversity compared to the NSGA-II optimisation framework.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 5, July 2009, Pages 9533–9538
نویسندگان
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