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2016 | OriginalPaper | Buchkapitel

Community Detection Based on an Improved Genetic Algorithm

verfasst von : Kangshun Li, Lu Xiong

Erschienen in: Computational Intelligence and Intelligent Systems

Verlag: Springer Singapore

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Abstract

When the traditional genetic algorithm was used to solve the community detection problem, it was not easy to avoid the problems of low efficiency and slow convergent speed. To be aim at these problems, a improved genetic algorithm which is based on the immune mechanism was proposed in this paper. In this new algorithm, the immune mechanism was used to ensure the diversity of population. Meanwhile, a improved character encoding was adopted to further reduce the search space. The results shows that the shortcomings of slow convergent speed and low efficiency could be overcome by using the improved genetic algorithm to solve these problems, compared with the traditional genetic algorithm.

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Vorheriges Kapitel A New Trend Peak Algorithm with X-ray Image for Wheel Hubs Detection and Recognition

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Titel: Community Detection Based on an Improved Genetic Algorithm
verfasst von: Kangshun Li
Lu Xiong
Verlag: Springer Singapore
Buch: Computational Intelligence and Intelligent Systems
Print ISBN: 978-981-10-0355-4

Electronic ISBN: 978-981-10-0356-1

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-981-10-0356-1_4

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