Abstract
A new scheme of detector generation and matching mechanism for negative selection algorithm is introduced featuring detectors with variable properties. While detectors can be variable in different ways using this concept, the paper describes an algorithm when the variable parameter is the size of the detectors in real-valued space. The algorithm is tested using synthetic and real-world datasets, including time series data that are transformed into multiple-dimensional data during the preprocessing phase. Preliminary results demonstrate that the new approach enhances the negative selection algorithm in efficiency and reliability without significant increase in complexity.
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Ji, Z., Dasgupta, D. (2004). Real-Valued Negative Selection Algorithm with Variable-Sized Detectors. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24854-5_30
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DOI: https://doi.org/10.1007/978-3-540-24854-5_30
Publisher Name: Springer, Berlin, Heidelberg
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