Clustering using levy flight cuckoo search

dc.contributor.authorSenthilnath, J.
dc.contributor.authorDas, V.
dc.contributor.authorOmkar, S.N.
dc.contributor.authorMani, V.
dc.date.accessioned2026-02-06T06:40:18Z
dc.date.issued2013
dc.description.abstractIn this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results are tabulated and analysed using various techniques. Finally we conclude that under the given set of parameters, cuckoo search works efficiently for majority of the dataset and levy flight plays an important role. © 2013 Springer.
dc.identifier.citationAdvances in Intelligent Systems and Computing, 2013, Vol.202 AISC, VOL. 2, p. 65-75
dc.identifier.issn21945357
dc.identifier.urihttps://doi.org/10.1007/978-81-322-1041-2_6
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/32817
dc.publisherSpringer Verlag service@springer.de
dc.subjectClustering
dc.subjectCuckoo search
dc.subjectGenetic algorithm
dc.subjectLevy flight
dc.subjectParticle swarm optimization
dc.titleClustering using levy flight cuckoo search

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