Special issue: Recent developments in hybrid intelligent systems: Guest-editorial
International Journal of Hybrid Intelligent Systems - Recent developments in Hybrid Intelligent Systems
A survey of image classification methods and techniques for improving classification performance
International Journal of Remote Sensing
The many facets of natural computing
Communications of the ACM
Recent advances in intelligent paradigms fusion and their applications
International Journal of Hybrid Intelligent Systems - Recent Advances in Intelligent Paradigms Fusion and Their Applications
Population distributions in biogeography-based optimization algorithms with elitism
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Biogeography-based optimization combined with evolutionary strategy and immigration refusal
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Nature-Inspired Metaheuristic Algorithms: Second Edition
Nature-Inspired Metaheuristic Algorithms: Second Edition
Blended biogeography-based optimization for constrained optimization
Engineering Applications of Artificial Intelligence
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Feature and algorithm selection with Hybrid Intelligent Techniques
International Journal of Hybrid Intelligent Systems - Feature and algorithm selection with Hybrid Intelligent Techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Development of Swarm Based Hybrid Algorithm for Identification of Natural Terrain Features
CICN '11 Proceedings of the 2011 International Conference on Computational Intelligence and Communication Networks
Biogeography-Based Optimization
IEEE Transactions on Evolutionary Computation
Evaluation of a new hybrid algorithm for highly imbalanced classification problems
International Journal of Hybrid Intelligent Systems
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This paper introduces a novel bio inspired clustering algorithm called Cuckoo Search Clustering Algorithm CSCA. This algorithm is based on the recently proposed Cuckoo Search Optimization technique which mimics the breeding strategy of the parasitic bird-cuckoo. The algorithm is further extended to a classification method, Biogeography Based Cuckoo Search Classification Algorithm BCSCA, which is a hybrid approach of the two nature inspired metaheuristic techniques. The proposed algorithms are validated with real time remote sensing satellite image datasets. The CSCA was first tested with benchmark dataset, which yields good results. Inspired by the results, it was applied on two real time remote sensing satellite image datasets for extraction of the water body, which itself is a quite complex problem. A new method for the generation of new cuckoos has been proposed, which is used in the algorithms. The resulting algorithm is conceptually simpler, takes less parameter than other nature inspired algorithms, and, after some parameter tuning, yields very good results. The extended algorithm BCSCA is also tested on the same satellite image for identifying different land covers by classifying the image in various classes. The algorithm was successful in classifying other land cover regions like rocky, barren, urban and vegetation. We strongly feel that results can be further improved by finer tuning of the parameters. Both the algorithms use Davies-Bouldin index DBI as fitness function. Further exploration of suggested algorithms CSCA and BCSCA may prove them to be strong entrants in the pool of nature inspired techniques.