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A new RBF neural network is presented to overcome the shortcoming that the training process of RBF neural network is slow in the paper. The immune genetic algorithm is combined with the RBF neural network to optimize the center of the RBF network, improve the definition method of affinity degree, and introduce adjusting factor based on density. Thus the learning efficiency and approximation precision...
According to rules of ants looking for food and immune genetic thought, an ant colony genetic algorithm is proposed based on immune mechanism. In precondition of keeping characteristics of the ant colony algorithm for global optimization and getting rationality of solutions in finite time, by introducing immune mechanism, the diversity of individuals can be assured and the phenomenon of long searching...
In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a single mutation operator, typically a Gaussian. A mixed mutation strategy may be more efficient than a single one. In view of this, a mixed mutation strategy using Gaussian and Cauchy mutations...
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