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Homogeneous pooling group delineation for flood frequency analysis using a fuzzy expert system with genetic enhancement

机译:使用具有遗传增强功能的模糊专家系统对洪水频率进行均质池群划分

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摘要

Pooled flood frequency analysis has been widely used to improve flood quantile estimation at sites that have short streamflow gauging records. When conducting pooled frequency analysis, it is necessary to delineate homogeneous pooling groups. A basic requirement for a pooling group is that the catchments in a pooling group should have sufficient similarity in hydrological response to provide a basis for information transfer. In this paper, methods using fuzzy expert systems (FES) are developed to derive an objective similarity measure between catchments. The steps for building the FES are explained in detail. The performance of the FES is improved by tuning of the membership functions of the fuzzy sets using a genetic algorithm. The proposed methods are applied to flood data from Great Britain and compared with results obtained from two other methods. The results indicate that the proposed FES methods have the capability of utilizing inputs from different categories of catchment characteristics and producing similarity measures that have high reliability. (C) 2004 Elsevier B.V. All fights reserved.
机译:汇总洪水频率分析已被广泛用于改善流量测量记录短的站点的洪水分位数估计。进行合并频率分析时,有必要划定齐次合并组。汇集小组的基本要求是汇集小组的流域在水文响应方面应具有足够的相似性,以便为信息传递提供基础。在本文中,开发了使用模糊专家系统(FES)的方法来得出流域之间的客观相似性度量。详细说明了构建FES的步骤。通过使用遗传算法调整模糊集的隶属函数,可以提高FES的性能。所提出的方法应用于来自英国的洪水数据,并与其他两种方法的结果进行了比较。结果表明,所提出的FES方法具有利用来自不同流域特征类别的输入并产生具有高可靠性的相似性度量的能力。 (C)2004 Elsevier B.V.版权所有。

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