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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Mirhosseini, M., Nezamabadi-pour, H. BICA: a binary imperialist competitive algorithm and its application in CBIR systems. Int. J. Mach. Learn. & Cyber. 9, 2043–2057 (2018). https://doi.org/10.1007/s13042-017-0686-4
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DOI: https://doi.org/10.1007/s13042-017-0686-4