Finding the representative in a cluster using correlation clustering

Nagy, Dávid; Aszalós, László; Mihálydeák, Tamás

doi:10.1556/606.2019.14.1.2

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…The clustering method should produce high quality clusters with a high intra-class similarity and a low inter-class similarity. The clustering is a widely used tool and is based on grouping objects where the objects in one group (cluster) are similar, and the objects from different groups are dissimilar [25].The quality of the clustering results depends on both the similarity measured by the method and its implementation.…”

Section: Regional Flood Frequency Analysismentioning

confidence: 99%

Comparison of two approaches for an estimation of the mean annual flood at ungauged sites in Slovakia

2020

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Regional flood frequency analysis is considered to be an important and popular method for estimating different hydrological variables at ungauged sites. The estimation of the index flood is the essential problem when this method is applied. The objective of the study is a comparison of the estimation of the mean annual flood (or index flood) by using two approaches based on the ‘so-called’ index flood method and top-kriging. The concept behind these methods permits estimating the mean annual flood at ungauged locations using information taken from gauged sites located within the same homogeneous pooling groups. The study area comprises 104 gauging stations on the whole territory of Slovakia. The observation period of the annual maximum discharges of the selected stations was from 1961-2010. The identification of the homogeneous pooling group was performed using a non-hierarchical k-means clustering algorithm. The optimal number of clusters is determined by the Silhouette method. As a result, eight homogeneous pooling group clusters were identified. Finally, the results of the estimated mean annual floods using the index flood method and top-kriging were compared with the observed data. Top-kriging provided better results than the classical index flood method for estimating the mean annual flood at ungauged sites.

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Section: Regional Flood Frequency Analysismentioning

confidence: 99%