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Clustering analysis of railway driving missions with niching

Jaafar, Amine and Sareni, Bruno and Roboam, Xavier Clustering analysis of railway driving missions with niching. (2012) COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 31 (3). 920-931. ISSN 0332-1649

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Official URL: http://dx.doi.org/10.1108/03321641211209807


A wide number of applications requires classifying or grouping data into a set of categories or clusters. Most popular clustering techniques to achieve this objective are K-means clustering and hierarchical clustering. However, both of these methods necessitate the a priori setting of the cluster number. In this paper, a clustering method based on the use of a niching genetic algorithm is presented, with the aim of finding the best compromise between the inter-cluster distance maximization and the intra-cluster distance minimization. This method is applied to three clustering benchmarks and to the classification of driving missions for railway applications.

Item Type:Article
Additional Information:Thanks to Emerald editor. The current issue and full text archive of this journal is available at www.emeraldinsight.com/0332-1649.htm
HAL Id:hal-00762266
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Laboratory name:
Deposited On:06 Dec 2012 16:20

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