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DC Field | Value | Language |
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dc.contributor.author | Senthilnath, J. | |
dc.contributor.author | Das, V. | |
dc.contributor.author | Omkar, S.N. | |
dc.contributor.author | Mani, V. | |
dc.date.accessioned | 2020-03-30T10:03:14Z | - |
dc.date.available | 2020-03-30T10:03:14Z | - |
dc.date.issued | 2013 | |
dc.identifier.citation | Advances in Intelligent Systems and Computing, 2013, Vol.202 AISC, VOL. 2, pp.65-75 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/7974 | - |
dc.description.abstract | In 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. | en_US |
dc.title | Clustering using levy flight cuckoo search | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 2. Conference Papers |
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