Cuckoo Search Clustering Algorithm: A novel strategy of biomimicry

A novel, nature inspired, unsupervised classification method, based on the most recent metaheuristic algorithm, stirred by the breeding strategy of the parasitic bird, the cuckoo, is introduced in this paper. The proposed Cuckoo Search Clustering Algorithm (CSCA) yields good results on benchmark dat...

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Bibliographic Details
Published in2011 World Congress on Information and Communication Technologies pp. 916 - 921
Main Authors Goel, S., Sharma, A., Bedi, P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2011
Subjects
Accuracy
Algorithm design and analysis
Benchmark testing
Clustering algorithms
Cuckoo Search Clustering Algorithm (CSCA)
Cuckoo Serach
Davies-Bouldin index (DBI)
Optimization
Remote sensing
Satellite Image
Satellites
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ISBN1467301272
9781467301275
DOI10.1109/WICT.2011.6141370

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Summary:A novel, nature inspired, unsupervised classification method, based on the most recent metaheuristic algorithm, stirred by the breeding strategy of the parasitic bird, the cuckoo, is introduced in this paper. The proposed Cuckoo Search Clustering Algorithm (CSCA) yields good results on benchmark dataset. Inspired by the results, the proposed algorithm is validated on two real time remote sensing satellite- image datasets for extraction of the water body, which itself is a quite complex problem. The CSCA makes use of Davies-Bouldin index (DBI) as fitness function. Also a method for generation of new cuckoos used in this algorithm is introduced. The resulting algorithm is conceptually simpler, takes less parameter than other nature inspired algorithms, and, after some parameter tuning, yields very good results.
ISBN:1467301272
9781467301275
DOI:10.1109/WICT.2011.6141370