A Parallel Coevolutionary Immune Neural Network and Its Application to Signal Simulation
The work is to propose a parallel coevolutionary immune neural network to decide weights and thresholds of feedforward network so as to deal with high dimensional or strongly nonlinear signal simulation. The network is developed based on the feedforward network, a novel simple artificial immune model, antibody representation, and coevolutionary ideas of antibody populations of the immune system, in which an evolution mechanism originated from humoral immune response is designed as a fundamental local evolution scheme.Through practical application and comparative analysis, numerical experiments illustrate that the proposed network can effectively simulate practical signal, and also be superior to the compared algorithms.
KeywordsGene Segment Feedforward Network Artificial Immune System Clonal Selection Algorithm Antibody Population
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