Dan Zhang1, Yu Zhang2, Yiwen Liang1,*
CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2317-2336, 2023, DOI:10.32604/cmc.2023.038026
Abstract The dendritic cell algorithm (DCA) is an excellent prototype for developing Machine Learning inspired by the function of the powerful natural immune system. Too many parameters increase complexity and lead to plenty of criticism in the signal fusion procedure of DCA. The loss function of DCA is ambiguous due to its complexity. To reduce the uncertainty, several researchers simplified the algorithm program; some introduced gradient descent to optimize parameters; some utilized searching methods to find the optimal parameter combination. However, these studies are either time-consuming or need to be revised in the case of non-convex… More >
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