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Rough particle swarm optimization and its applications in data mining

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Abstract

This paper proposes a novel particle swarm optimization algorithm, rough particle swarm optimization algorithm (RPSOA), based on the notion of rough patterns that use rough values defined with upper and lower intervals that represent a range or set of values. In this paper, various operators and evaluation measures that can be used in RPSOA have been described and efficiently utilized in data mining applications, especially in automatic mining of numeric association rules which is a hard problem.

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Authors and Affiliations

  1. Department of Computer Engineering, Faculty of Engineering, Firat University, 23119, Elazig, Turkey

    Bilal Alatas & Erhan Akin

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  1. Bilal Alatas
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  2. Erhan Akin
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Correspondence to Bilal Alatas.

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Alatas, B., Akin, E. Rough particle swarm optimization and its applications in data mining. Soft Comput 12, 1205–1218 (2008). https://doi.org/10.1007/s00500-008-0284-1

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