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The traditional fusion algorithms, such as principal component analysis, wavelet transform, Gauss-Laplacian pyramids, Brovey transform, curvelet transform and so on, set down the fusion rules before fusion process. However, the rules which determine the attributes of fusion results cannot be adjusted according to different application. In this paper, a(More)
— In order to increase the diversity of immune algorithm when solving high-dimensional global optimization problems, a novel clonal selection algorithm with randomized clonal expansion strategy(RCSA) is proposed. The main characteristic of RCSA is clonal expansion. In addition, a novel performance evaluation criterion is constructed in this paper, by which(More)
The clone selection algorithm (CSA) is a stochastic, population-based evolutionary method that can be applied to the global optimization problems. The paper proposes a variation on the traditional CSA: clone selection algorithm with simplex crossover, or CSA_SPX. The novel algorithm employs the randomized distribution scheme for clone individuals, bit(More)
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