Ayodele Lasisi1,*, Ali M. Aseere2
Computer Systems Science and Engineering, Vol.38, No.2, pp. 183-195, 2021, DOI:10.32604/csse.2021.015275
Abstract The negative selection algorithm (NSA) is an adaptive technique inspired by how the biological immune system discriminates the self from non-self. It asserts itself as one of the most important algorithms of the artificial immune system. A key element of the NSA is its great dependency on the random detectors in monitoring for any abnormalities. However, these detectors have limited performance. Redundant detectors are generated, leading to difficulties for detectors to effectively occupy the non-self space. To alleviate this problem, we propose the nature-inspired metaheuristic cuckoo search (CS), a stochastic global search algorithm, which improves the random generation of detectors… More >
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