A new feature selection algorithm based on Immune Clonal selection algorithm (ICSA) is proposed.
提出了一种基于免疫克隆选择算法的特征选择方法。
The simulation results show that ICSA based on this method of mutation can improve the rapidity of learning BP network well and avoid prematurity effectively.
仿真实验表明，基于这种变异方法的免疫克隆选择算法可以很好地提高BP网络的学习速度，有效地避免算法过早收敛的问题。
By introducing the information processing mechanism of artificial immune systems and neural network to CSA, an immune clonal selection algorithm (ICSA) was proposed.
把人工免疫系统和神经网络系统的信息处理机制引入到CSA提出了免疫克隆选择算法。
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