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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 12/2018

28-04-2017 | Original Article

BICA: a binary imperialist competitive algorithm and its application in CBIR systems

Authors: Mina Mirhosseini, Hossein Nezamabadi-pour

Published in: International Journal of Machine Learning and Cybernetics | Issue 12/2018

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Abstract

Imperialist Competitive Algorithm (ICA), which is a mathematical model and the computer simulation of human social evolution, works as a successful algorithm in many optimization problems. In this paper a new binary version of imperialist competitive algorithm, namely BICA is proposed using a well appropriated transfer function and optimal parameter setting. These allow the algorithm to explore a larger number of possible solutions and avoid the stagnation. To assess the performance of the proposed method the 0–1 knapsack problem, the feature selection problem and the Content-Based Image Retrieval (CBIR) systems are experienced; and the effectiveness of this method is compared with the state-of-the-art algorithms. Comparative results confirm the performance of the proposed BICA in all three applications.
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Metadata
Title
BICA: a binary imperialist competitive algorithm and its application in CBIR systems
Authors
Mina Mirhosseini
Hossein Nezamabadi-pour
Publication date
28-04-2017
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 12/2018
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-017-0686-4

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