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This paper proposes a particle swarm optimization (PSO)-based detector optimization scheme in the negative selection algorithm (NSA). The NSA is a natural immune response inspired pattern discrimination method. In the new scheme, the NSA detectors are optimized by the PSO to collectively occupy the maximal coverage of the nonself space so that they can achieve the best anomaly detection performance...
This paper proposes a genetic algorithms (GA) based detector optimization scheme in the negative selection algorithm (NSA). The NSA is a natural immune response inspired pattern discrimination method. In our scheme, the NSA detectors are optimized by the GA to occupy the maximal coverage of the nonself space so that they can achieve the best anomaly detection performance. Two numerical examples including...
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