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Weighted fuzzy kernel-clustering algorithm with adaptive differential evolution and its application on flood classification

机译:自适应差分进化加权模糊聚类算法及其在洪水分类中的应用

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摘要

Flood classification is the fundamental problem of flood risk analysis and plays an important role in flood disaster risk management. Considering the fact that flood classification is a problem of multi-attribute and multi-stage fuzzy synthetically evaluation, this paper mainly proposed the weighted fuzzy kernel-clustering algorithm (WFKCA) with adaptive differential evolution algorithm (ADE) to solve this problem. Firstly, WFKCA is detailed introduced, and then the differential evolution algorithm (DE) is applied for the fuzzy clustering, thus to obtain the better results. Taking into consideration the disadvantage of DE, ADE is present after the introduction of DE. Finally, the combination of WFKCA and ADE is applied for flood classification, and the results demonstrated the methodology is reasonable and reliable, thus provide a new effective approach for flood classification.
机译:洪水分类是洪水风险分析的根本问题,在洪水灾害风险管理中具有重要作用。考虑到洪水分类是一个多属性,多阶段的模糊综合评价问题,主要提出了加权模糊核聚类算法(WFKCA)和自适应差分进化算法(ADE)来解决这一问题。首先详细介绍了WFKCA,然后将差分进化算法(DE)应用于模糊聚类,从而获得较好的结果。考虑到DE的缺点,在引入DE后出现了ADE。最后,将WFKCA和ADE相结合进行洪水分类,结果表明该方法合理可靠,为洪水分类提供了一种新的有效途径。

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